Search

In this paper, we propose a novel 30-dimension descriptor named SIFTRO(SIFT of Ring Order) to promote the matching speed, which is generated from 3 local ring areas. A new element reordering method is presented to ensure the descriptor’s rotation invariance. To obtain the best scale factor for SIFTRO descriptor, the weight hierarchy decision model based on AHP is designed. The experiments show that the SIFTRO descriptor inherits the advantages of the invariance to image scaling, rotation and affine, and it also speeds up greatly in image matching, while the precision is improved compared with that of original SIFT.

We theoretically analyze the characteristics of scale factor in frequency sensitive integrated optical gyroscope consisting of a ring resonator coupled with double ring resonators. The impact of through coupling coefficients is investigated to decide the optimal parameters located at 0s-1 for improving the scale factor. It demonstrates that the scale factor enhancement in this frequency sensitive optical gyroscope, without increasing the overall footprint, can be improved compared with conventional single ring resonator gyroscope and presents the characteristic of better performance within low-rate range. It implies a broad prospect in highly integrated on-chip applications, especially in aeronautic and astronautic area.

Scale estimation of objects is a challenging problem in image processing. This work presents a novel method to detect and estimate the scaling factor of a target in an observed scene corrupted with additive noise and clutter. Given a set of available views of the target the proposed method is able to detect the target and estimate its scaling factor using a template matched filters and a scale pyramidal representation. The performance of the proposed method is evaluated in synthetic and real-life scenes in different pattern recognition applications. The obtained results are characterized in terms of objective metrics.

Fiber optical gyro (FOG) is a kind of solid-state optical gyroscope with good environmental adaptability, which has been widely used in national defense, aviation, aerospace and other civilian areas. In some applications, FOG will experience environmental conditions such as vacuum, radiation, vibration and so on, and the scale-factor performance is concerned as an important accuracy indicator. However, the scale-factor performance of FOG under these environmental conditions is difficult to test using conventional methods, as the turntable can't work under these environmental conditions. According to the phenomenon that the physical effects of FOG produced by the sawtooth voltage signal under static conditions is consistent with the physical effects of FOG produced by a turntable in uniform rotation, a new method for the scale-factor performance test of FOG without turntable is proposed in this paper. In this method, the test system of the scale-factor performance is constituted by an external operational amplifier circuit and a FOG which the modulation signal and Y waveguied are disconnected. The external operational amplifier circuit is used to superimpose the externally generated sawtooth voltage signal and the modulation signal of FOG, and to exert the superimposed signal on the Y waveguide of the FOG. The test system can produce different equivalent angular velocities by changing the cycle of the sawtooth signal in the scale-factor performance test. In this paper, the system model of FOG superimposed with an externally generated sawtooth is analyzed, and a conclusion that the effect of the equivalent input angular velocity produced by the sawtooth voltage signal is consistent with the effect of input angular velocity produced by the turntable is obtained. The relationship between the equivalent angular velocity and the parameters such as sawtooth cycle and so on is presented, and the correction method for the equivalent angular velocity is also presented by analyzing the influence of each parameter error on the equivalent angular velocity. A comparative experiment of the method proposed in this paper and the method of turntable calibration was conducted, and the scale-factor performance test results of the same FOG using the two methods were consistent. Using the method proposed in this paper to test the scale-factor performance of FOG, the input angular velocity is the equivalent effect produced by a sawtooth voltage signal, and there is no need to use a turntable to produce mechanical rotation, so this method can be used to test the performance of FOG at the ambient conditions which turntable can not work.

Due to the increase in production of the angle transducers characterized by high accuracy and high speed of operation [1], there arises a need for metrological control of their function parameters. This challenge can be successfully met involving the dynamic goniometer systems (DG), which consist of the optical angle encoder (OAE) or the ring laser (RL) [2]. The dynamic laser goniometer systems [2], the scale of which is produced by the ring laser, can be successfully used for calibration of the angle encoders. The ring laser operating in the mode of the angle measurement during its rotation has a number of undeniable advantages, such as high degree of uniformity and potential accuracy. However, alongside with the advantages it has several limitations, such as the measurement error increase at low rotation velocity values and instability of the angular scale factor [2]. Integrating the ring laser and the optical angle sensor, the angular scale of which is characterized by a considerably lower uniformity, but a greater degree of stability, provides for the studying of the metrological characteristics of the dynamic goniometer, expansion of the range or its angular operation velocity and its operation in static mode. The articles covers the issues of constructing the dynamic goniometer for calibration of angle encoders as well as the methods and results of its studies.

It is frequently necessary in archaeology to map excavated features so their structure can be recorded before they are dismantled in order for the excavation to continue. This process can be time consuming, error prone and manually intensive. Three-dimensional recording devices, which have the advantage of being faster, less labor intensive and more detailed, present an attractive alternative method of mapping. A small, portable hand scanner such as the DotProduct DPI-7, could be used for this purpose. However, the three-dimensional data collected from this device contain systematic distortions that cause errors in the recorded shape of the features being mapped. The performance of the DPI-7 scanner is evaluated in this paper using self-calibration based techniques. A calibration field consisting of spherical targets rigidly mounted on a planar background was imaged from multiple locations, and the target deviations from expected locations are used to quantify the performance of the device. The largest source of systematic error in the DPI-7 data was found to be a scale error affecting dimensions orthogonal to the depth. These in-plane distortions were modeled using a single scale factor parameter in the self-calibration solution, resulting in a 54% reduction in the RMS coordinate errors.

In dynamic condition, scale factor has been one of the main errors for MEMS (micro electromechanical system) gyroscopes. This paper, based on one kind of gyroscope in the airborne optoelectronic pod, studies the variation law of the scale factor and its compensation under different environment temperature and operating speed, and then puts forward to the method of combination of ambient temperature and actual angular velocity when compensating the MEMS gyroscope’s scale factor error. Test result demonstrates that the scale factor error can be effectively suppressed, and compared with compensation method only based on temperature or angular velocity separately, this new method is easy practical and presents better performance.

In most cases of the generation of computer-generated hologram, a zero-valued dummy area is usually added to the desired object in order to avoid the disturbance of high order reconstruction. The high order reconstruction not only disturbs the zero order reconstruction but also decreases the zero order reconstruction diffraction efficiency. In this study, we show a method to improve the zero order reconstruction diffraction efficiency by using a finite dummy area. According to the structure of a general computer-generated hologram, that is each calculated computer-generated hologram point has the same square size, then the high order reconstruction is the product of the zero order reconstruction and a sampling function with a scale factor. We use computer simulation to show the effect of dummy area in the improvement of the zero order reconstruction diffraction efficiency. According to our simulation results, we find that the zero order reconstruction diffraction efficiency increases as increasing the size of dummy area. In addition, we also find that the on-axis reconstruction has a higher reconstruction diffraction efficiency that the off-axis ones.

Differential Evolution (DE) is a simple yet efficient stochastic algorithm for solving real world problems. However, the performance of DE is sensitive to the mutation and crossover strategies and their associated parameters. In this paper, a kind of scale factor generating scheme within the process of search is proposed, named MSFDE, to enhance the performance of DE. In this method, the scale factor is a D dimensional matrix which component is a random number for each difference vector during the iteration. The proposed scheme has been evaluated on a test-suite of 25 benchmark functions provided by CEC 2005 special session on real parameter optimization. The results of the experiments indicate that MDVDE is competitive to classical DE and some other variants on different strategies.

The paper proposes a method to measure vibration amplitude of ultrasonic horn which is a very important component in the spindle for micro-electrical-chemical discharging machining. The method of image measuring amplitude on high frequency vibration is introduced. Non-contact measurement system based on vision technology is constructed. High precision location algorithm on image centroid, quadratic location algorithm, is presented to find the center of little light spot. Measurement experiments have been done to show the effect of image measurement technique on vibration amplitude of ultrasonic horn. In the experiments, precise calibration of the vision system is implemented using a normal graticule to obtain the scale factor between image pixel and real distance. The vibration amplitude of ultrasonic horn is changed by modifying the voltage amplitude of pulse power supply. The image of feature on ultrasonic horn is captured and image processing is carried out. The vibration amplitudes are got at different voltages.

Fiber-Optic Gyroscope (FOG) scale factor nonlinear error will result in errors in Strapdown Inertial Navigation System (SINS). In order to reduce nonlinear error of FOG scale factor in SINS, a compensation method is proposed in this paper based on curve piecewise fitting of FOG output. Firstly, reasons which can result in FOG scale factor error are introduced and the definition of nonlinear degree is provided. Then we introduce the method to divide the output range of FOG into several small pieces, and curve fitting is performed in each output range of FOG to obtain scale factor parameter. Different scale factor parameters of FOG are used in different pieces to improve FOG output precision. These parameters are identified by using three-axis turntable, and nonlinear error of FOG scale factor can be reduced. Finally, three-axis swing experiment of SINS verifies that the proposed method can reduce attitude output errors of SINS by compensating the nonlinear error of FOG scale factor and improve the precision of navigation. The results of experiments also demonstrate that the compensation scheme is easy to implement. It can effectively compensate the nonlinear error of FOG scale factor with slightly increased computation complexity. This method can be used in inertial technology based on FOG to improve precision.

A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.

Expanding image by an arbitrary scale factor and thereby creating an enlarged image is a crucial image processing operation. De-interlacing is an example of such operation where a video field is enlarged in vertical direction with 1 to 2 scale factor. The most advanced de-interlacing algorithms use a few consequent input fields to generate one output frame. In order to save hardware resources in video processors, missing lines in each field may be generated without reference to the other fields. Line doubling, known as “bobbing”, is the simplest intra field de-interlacing method. However, it may generate visual artifacts. For example, interpolation of an inserted line from a few neighboring lines by vertical filter may produce such visual artifacts as “jaggies.” In this work we present edge adaptive image up-scaling and/or enhancement algorithm, which can produce “jaggies” free video output frames. As a first step, an edge and its parameters in each interpolated pixel are detected from gradient squared tensor based on local signal variances. Then, according to the edge parameters including orientation, anisotropy and variance strength, the algorithm determines footprint and frequency response of two-dimensional interpolation filter for the output pixel. Filter’s coefficients are defined by edge parameters, so that quality of the output frame is controlled by local content. The proposed method may be used for image enlargement or enhancement (for example, anti-aliasing without resampling). It has been hardware implemented in video display processor for intra field de-interlacing of video images.

We recently reported good results with our image interpolation algorithm, One-Dimensional Control Grid Interpolation (1DCGI), in the context of grayscale images. 1DCGI has high quantitative accuracy, flexibility with respect to scaling factor, and low computational cost relative to similarly performing methods. Here we look to extend our method to the demosaicing of Bayer-Patterned images. 1DCGI-based demosaicing performs quantitatively better than the gradient-corrected linear interpolation method of Malvar. We also demonstrate effective interpolation of full color images.

In this work we analyze the compression and equalization of pulses in the ps range by using an approach based on the Radon-Wigner transform (RWT). The whole RWT display is obtained from a generalization of the Fourier transform, namely the fractional Fourier transform (FRT), by varying the fractional order p from 0 (temporal information) to 1 (spectral information). From the inspection of the RWT the optimum fractional order pC originating the desired processing condition can be obtained. However, as this signal representation depends on a scale factor which should be introduced, the value of pC is also affected. This point is here analyzed taking into account the restrictions on the scale factor which are imposed by the photonic devices involved in an experimental implementation; namely, an amount of chromatic dispersion and an attainable phase modulation factor. We illustrate the method with some applications which are of interest in fiber optic links such as second and third order chromatic dispersion compensation and pulse transmission under a non linear regime. The theoretical model derived from an analytical expression of the FRT is corroborated with numerical simulations.

The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

In order to identify accelerometer error model coefficients more accurately on indexing table, the relationship between the calibration accuracy of accelerometer and the errors of indexing table is determined. At first, the attitude matrix between accelerometer coordinate system and geographical coordinate system is established based on consideration of various error sources. Then the accelerometer output expressions are analyzed based on the established error model. After that, according to the output of an accelerometer, the relationship among calibration errors of accelerometer model coefficients, indexing table errors and alignment errors is analyzed through Fourier analysis. Finally, an accelerometer is calibrated on indexing table and the angular errors are measured, modifications of bias K F and scale factor K 1 are analyzed before and after compensating for the angular errors. Experiments show that, to make relative calibration accuracys of K F /K I and ΔK I /K I achieve relative accuracy of 10- 6 , the first and the second order term of Fourier series of the angular errors of the indexing table should be less than 0.15" and 0.4"separately, random error and angular rotary error of the axis system should be limited to 1" level.

Image mosaicking is the process of piecing together multiple video frames or still images from a moving camera to form a wide-area or panoramic view of the scene being imaged. Mosaics have widespread applications in many areas such as security surveillance, remote sensing, geographical exploration, agricultural field surveillance, virtual reality, digital video, and medical image analysis, among others. When mosaicking a large number of still images or video frames, the quality of the resulting mosaic is compromised by projective distortion. That is, during the mosaicking process, the image frames that are transformed and pasted to the mosaic become significantly scaled down and appear out of proportion with respect to the mosaic. As more frames continue to be transformed, important target information in the frames can be lost since the transformed frames become too small, which eventually leads to the inability to continue further. Some projective distortion correction techniques make use of prior information such as GPS information embedded within the image, or camera internal and external parameters. Alternatively, this paper proposes a new algorithm to reduce the projective distortion without using any prior information whatsoever. Based on the analysis of the projective distortion, we approximate the projective matrix that describes the transformation between image frames using an affine model. Using singular value decomposition, we can deduce the affine model scaling factor that is usually very close to 1. By resetting the image scale of the affine model to 1, the transformed image size remains unchanged. Even though the proposed correction introduces some error in the image matching, this error is typically acceptable and more importantly, the final mosaic preserves the original image size after transformation. We demonstrate the effectiveness of this new correction algorithm on two real-world unmanned air vehicle (UAV) sequences. The proposed method is shown to be effective and suitable for real-time implementation.

Perceptual image distortion measures can play a fundamental role in evaluating and optimizing imaging systems and image processing algorithms. Many existing measures are formulated to represent "just noticeable differences" (JNDs), as measured in psychophysical experiments on human subjects. But some image distortions, such as those arising from small changes in the intensity of the ambient illumination, are far more tolerable to human observers than those that disrupt the spatial structure of intensities and colors. Here, we introduce a framework in which we quantify these perceptual distortions in terms of "just intolerable differences" (JIDs). As in (Wang & Simoncelli, Proc. ICIP 2005), we first construct a set of spatio-chromatic basis functions to approximate (as a first-order Taylor series) a set of "non-structural" distortions that result from changes in lighting/imaging/viewing conditions. These basis functions are defined on local image patches, and are adaptive, in that they are computed as functions of the undistorted reference image. This set is then augmented with a complete basis arising from a linear approximation of the CIELAB color space. Each basis function is weighted by a scale factor to convert it into units corresponding to JIDs. Each patch of the error image is represented using this weighted overcomplete basis, and the overall distortion metric is computed by summing the squared coefficients over all such (overlapping) patches. We implement an example of this metric, incorporating invariance to small changes in the viewing and lighting conditions, and demonstrate that the resulting distortion values are more consistent with human perception than those produced by CIELAB or S-CIELAB.

This essay proposes a method for camera calibration. This method calibrates camera's all intrinsic parameters and extrinsic parameters step-by-step under the condition of considering the first order radial distortion. Compared with Tsai's two-stage method, this method only needs to use a coplanar target and can calibrate the image center and the scale factor. It also introduces a new distortion model and then can completely calibrate camera linearly, avoiding the trouble and the instability of non-linear optimization. It's simpler. Then, this essay introduces a computing model of three-dimensional reconstruction of the two cameras' system, and proves that this calibration method has high accuracy after the three-dimensional reconstruction.

This paper proposes, for the first time, a MEMS-based digitally tunable micromechanical resonator (DTMR). A general methodology of tuning the resonant frequency of a MEMS comb-driven resonator using digital voltages is presented. In this mechanism, a microelectromechanical digital-to-analog converter (MEMDAC) is employed as the tuning unit. The resonant frequency of the DTMR shifts in response to the input digital voltage. Several structures have been proposed, while the one using the number of the vertical beams as the scale factor features the optimum linearity. In a modified design, the resonate frequency can be tuned from approximately 65 to 94 kHz. The maximum deviation from ideal linearity can be reduced to 0.31 kHz, which is remarkably less than those of the preliminary designs.

Image Registration is the process of fusing or overlaying of two images of the same scene that were taken at different times and/or from different viewing angles and/or by sensors with different modality or resolution. The variations in the imaging environment induce the difference between the images of the same scene. In our situation, we have two images of the same scene taken with different sensors, one image is in the visible domain and the other is an IR image. The images are captured using a visible camera and a thermal camera by placing the two devices adjacent to each other and taking the images simultaneously without a significant change in time and spatial location. Using image registration we project the visible image into the infrared image to rectify both images to the same co-ordinate system. This is done to match the sensor output and then produce an information product from the two which can be used to further analyze and assess the scene. In this paper we use the conformal log polar mapping (CLPM) for image registration. The CLPM is invariant to changes in rotation and scale: rotational changes map to a shift along one of the axes and scale changes a shift long the other. Thus the CLPM for the two images mentioned above should essentially be the same even though the two were taken from different sensors. The amount of shift can be used to determine the angle of rotation of the rotated image with respect to the original image. The same holds for the change in scale of the two images were the shift along the x-axis or the magnitude axis in the log polar mappings of the two images can be used to find the scaling factor between the two images. This method calculates the transformation parameters for rectifying the reference image to the original image or vice-versa, and can be used to register the two images that vary in phase and scale. In this paper, we present a robust approach for image registration that uses these shifts to compute the parameters representing rotation and scale change, and registers a pair of images. An application of this approach is in detecting wave height for efficient navigation of a watercraft where the images to be fused are taken from multiple sensors which are fixed on the craft. The wave parameters can be determined by looking at the common features in the edge profile of the images taken from different sensors. The goal here is to provide real time assessment of the sea state from the information obtained from the sensor suite for possible route and speed changes to increase safety and improve ride quality.

In this paper, an adaptive image enhancement method based on neural networks is proposed. The low frequency components of the image can be obtained by average filter and the high frequency components of the image are obtained by subtracting the low frequency from the original image. The enhanced image is obtained by adding the original image to the high frequency components multiplied by the scale factor. The masking size of the average filter and the scale factor are given by the constructed neural net in terms of the mean and standard deviation of the image. Real experiments has been to test the proposed method and very good result has been obtained.

The Combined Array for Research in Millimeter-wave Astronomy (CARMA) have carried out a water vapor radiometer (WVR) project to test the WVR phase correction technique for better observational effciency. We have built two uncooled, but temperature-regulated, 22 GHz WVR prototypes to explore the feasibility of the technique. To better isolate the effects of instrumental and atmospheric instabilities, we have optimized theWVR design for simplicity with less high frequency components. The calibration system is Dicke switch with a single ambient load. The thermal regulation system consists of heaters and multi-stage insulation. We have completed testing of the WVR prototypes in a laboratory and at the CARMA site. The gain stability is about 20-100 mK and the front-end temperature rms is about a few mK to hundreds, depending on weather conditions. Based on the site tests, the sky temperature at 22 GHz usually varies a few K in 15 minutes, which is not necessary due to the atmospheric water vapor. Such short time-scale background temperature variation overwhelms the limit of the WVR dynamic range. Moreover, we have compared the WVR data rms with the phase monitor at the site and obtain a scale factor of the 22 GHz water vapor line, 6-12, which is consistent with the results of other WVR projects. We suggest that expanding the WVR dynamic range with diode detector models and a better thermal regulation system are keys to the success of the CARMA WVR phase correction.

In this paper, we extend our camera identification technology based on sensor noise to a more general setting when the image under investigation has been simultaneously cropped and scaled. The sensor fingerprint detection is formulated using hypothesis testing as a two-channel problem and a detector is derived using the generalized likelihood ratio test. A brute force search is proposed to find the scaling factor which is then refined in a detailed search. The cropping parameters are determined from the maximum of the normalized cross-correlation between two signals. The accuracy and limitations of the proposed technique are tested on images that underwent a wide range of cropping and scaling, including images that were acquired by digital zoom. Additionally, we demonstrate that sensor noise can be used as a template to reverse-engineer in-camera geometrical processing as well as recover from later geometrical transformations, thus offering a possible application for re-synchronizing in digital watermark detection.

This paper presents a technique for coding high dynamic range videos. The proposed coding scheme is scalable, such that both standard dynamic range and high dynamic range representations of a video can be extracted from one bit stream. A localized inverse tone mapping method is proposed for efficient inter-layer prediction, which applies a scaling factor and an offset to each macroblock, per color channel. The scaling factors and offsets are predicted from neighboring macroblocks, and then the differences are entropy coded. The proposed inter-layer prediction technique is independent of the forward tone mapping method and is able to cover a wide range of bit-depths and various color spaces. Simulations are performed based on H.264/AVC SVC common software and core experiment conditions. Results show the effectiveness of the proposed method.

The scale-invariant feature detecting methods always require a lot of computation yet sometimes still fail to meet the real-time demands in robot vision fields. To solve the problem, a quick method for detecting interest points is presented. To decrease the computation time, the detector selects as interest points those whose scale normalized Laplacian values are the local extrema in the nonholonomic pyramid scale space. The descriptor is built with several subregions, whose width is proportional to the scale factor, and the coordinates of the descriptor are rotated in relation to the interest point orientation just like the SIFT descriptor. The eigenvector is computed in the original color image and the mean values of the normalized color g and b in each subregion are chosen to be the factors of the eigenvector. Compared with the SIFT descriptor, this descriptor's dimension has been reduced evidently, which can simplify the point matching process. The performance of the method is analyzed in theory in this paper and the experimental results have certified its validity too.

To get an accurate scale factor of optical odometer, a method aided by DGPS is proposed, and the error compensation for the longitudinal position of optical odometer in vehicle navigation system is further studied. First, the tested data are preprocessed. Although the resolution of optical odometer is less than 2mm, the output noise affected by vehicle shaking attains to 2cm. Because of this, data is reconstructed based on kinematics analysis. The tested data are replaced with reconstructed data if the difference is larger than a threshold. The results show that by this method, the precision of ranging and speed can be improved efficiently, which is less than 0.002m and 0.04m/s respectively. If the output pulse number of odometer and the travel mileage are known, the scale factor can be calculated. The error is obtained through comparing the position data recorded by DGPS with the product of pulse number and the scale factor. It is shown that the linear correlation is remarkable between the data of error and velocity. Therefore the first order model and second order model are established. The compensated results indicate that the longitudinal positioning error can be controlled under 0.2m.

The effect of the dispersion of Verdet constant of ZF-7 optical glass upon the sensitivity of a bulk-glass optical current sensor are theoretically analyzed taking the Jones' Matrix as a mathematical tool and simulated with a computer. The investigation results show that the dispersion will obviously affect the scale factor of the current sensor. Therefore, it is necessary to stabilize the driving current and the ambient temperature of the optical source by some technical means. These results might be useful for the researchers and designers working in the optical current transforming techniques area.

Ab initio quantum trajectory simulations of a cavity QED system comprising an atomic beam traversing a coherently driven standing-wave cavity are carried out. The intensity correlation function in transmission is computed and compared with the experimental measurements of Rempe et al . [Phys. Rev. Lett. 67 , 1727 (1991)] and Foster et al . [Phys. Rev. A 61 , 053821 (2000)]. It is shown that atomic beam density fluctuations induced by the motion of the atoms can account for the reported disagreement of the experimental results with theory (by an overall scale factor of 2 to 4). Moderate misalignments of the atomic beam produce large intracavity photon number fluctuations which significantly degrade the quantum correlations. One parameter fits to the experimental data are made in the weak-field limit with the adjustable parameter being the atomic beam tilt. Departures of the experimental conditions from the weak-field limit are discussed.

For objects on a plane, a "scale factor" relates the physical dimensions of the objects to the corresponding dimensions in a camera image. This scale factor may be the only calibration parameter of importance in many test applications. The scale factor depends on the angular size of a pixel of the camera, and also on the range to the object plane. A measurement procedure is presented for the determination of scale factor to high precision, based on the translation of a large-area target by a precision translator. A correlation analysis of the images of a translated target against a reference image is used to extract image shifts and the scale factor. The precision of the measurement is limited by the translator accuracy, camera noise and various other secondary factors. This measurement depends on the target being translated in a plane perpendicular to the optic axis of the camera, so that the scale factor is constant during the translation. The method can be extended to inward-looking 3D camera networks and can, under suitable constraints, yield both scale factor and transcription angle.

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

In this paper, we propose a closed loop Micro-Opto-Electro-Mechanical (MOEM) accelerometer employing a nonuniform cantilever beam and an Anti Resonant Reflecting Optical Waveguide (ARROW) on silicon. The MOEM acelerometer consists of a Mach Zehnder Intereferometer (MZI) and an electro-elasto-optic phase modulator to nullify the acceleration induced phase change so as to make the device work in closed loop form. It is shown that MOEM accelerometers with noise equivalent acceleration of 0.255 µg/ \surd Hz, a dynamic range of 160g, scale factor stability of 1.57 ppm/°C and shock survivability of more than 1000 g is feasible.

We investigate how visual motion registered during one's own movement through a structured world can be used to gauge travel distance. Estimating absolute travel distance from the visual flow induced in the optic array of a moving observer is problematic because optic flow speeds co-vary with the dimensions of the environment and are thus subject to an environment specific scale factor. Discrimination of the distances of two simulated self-motions of different speed and duration is reliably possible from optic flow, however, if the visual environment is the same for both motions, because the scale factors cancel in this case. Here, we ask whether a distance estimate obtained from optic flow can be transformed into a spatial interval in the same visual environment. Subjects viewed a simulated self-motion sequence on a large (90 by 90 deg) projection screen or in a computer animated virtual environment (CAVE) with completely immersive, stereographic, head-yoked projection, that extended 180deg horizontally and included the floor space in front of the observer. The sequence depicted self-motion over a ground plane covered with random dots. Simulated distances ranged from 1.5 to 13 meters with variable speed and duration of the movement. After the movement stopped, the screen depicted a stationary view of the scene and two horizontal lines appeared on the ground in front of the observer. The subject had to adjust one of these lines such that the spatial interval between the lines matched the distance traveled during the movement simulation. Adjusted interval size was linearly related to simulated travel distance, suggesting that observers could obtain a measure of distance from the optic flow. The slope of the regression was 0.7. Thus, subjects underestimated distance by 30%. This result was similar for stereoscopic and monoscopic conditions. We conclude that optic flow can be used to derive an estimate of travel distance, but this estimate is subject to scaling when compared to static intervals in the environment, irrespective of steroscopic depth cues.

The effects of the linear birefringence inside a bulk glass current sensing element and the incident polarizing angle upon the performance of a bulk glass optical current sensor are derived and analyzed theoretically. The investigation results show that the linear birefringence will modify the scale factor of the system with a sample function; it can also affect the extent of the influence of the incident polarizing angle, at the same time. When the incident polarizing angle has some special values such as 0, 45, or 90 degree, its effect to the system will be zero. These results might provide some useful reference to the researchers and designers of bulk glass optical current sensors.

Micro-Opto-Electro-Mechanical (MOEM) accelerometers employing a cantilever beam and anti resonant reflecting optical waveguide (ARROW) on a silicon is analyzed. Two types of MOEM accelerometers and a closed loop operation that can enhance the performance significantly compared to MEMS accelerometer is presented. As a typical example our study shows a MOEM accelerometer with a minimum detectable acceleration of 0.255 μ g/√Hz, a dynamic range of 160g, scale factor stability of 1.57 ppm/°c and shock survivability of more than 1000 g.

Quantization-based watermarking schemes are vulnerable to amplitude scaling. Therefore the scaling factor has to be accounted for either at the encoder, or at the decoder, prior to watermark decoding. In this paper we derive the marginal probability density model for the watermarked and attacked data, when the attack channel consists of amplitude scaling followed by additive noise. The encoder is Quantization Index Modulation with Distortion Compensation. Based on this model we obtain two estimation procedures for the scale parameter. The first approach is based on Fourier Analysis of the probability density function. The estimation of the scaling parameter relies on the structure of the received data. The second approach that we obtain is the Maximum Likelihood estimator of the scaling factor. We study the performance of the estimation procedures theoretically and experimentally with real audio signals, and compare them to other well known approaches for amplitude scale estimation in the literature.

A triaxial accelerometer calibration technique that evades the problems of the conventional calibration method of aligning with gravity is proposed in this paper. It is based on the principle that the vector sum of acceleration from three sensing axes should be equal to the gravity vector. The method requires the accelerometer to be oriented and stationary in 6 different ways to solve for the 3 scale factors and 3 offsets. The Newton-Raphson method was employed to solve the non-linear equations in order to obtain the scale factors and offsets. The iterative process was fast, with an average of 5 iterations required to solve the system of equations. The accuracy of the derived scale factors and offsets were determined by using them to calculate the gravity vector magnitude using the triaxial accelerometer to measure gravity. The triaxial accelerometer was used to measure gravity 264 times to determine the accuracy of the 44 acceptable sets of scale factors and offsets derived from the calibrations (gravity was assumed to equal 9.8000 ms-2 during the calibration). It was found that the best calibration calculated the gravity vector magnitude to 9.8156 ± 0.4294 ms-2. This equates to a maximum of 4.5% error in terms of a constant acceleration measurement. Because of the principle behind this method, it has the disadvantage that noise/error in only one axis will cause an inaccurate determination of all the scale factors and offsets.

Electronic distance measuring instruments (EDM) are now universally used for measuring large engineering structures such as ships, dams and tunnels and still have a key role for establishing position in land surveying where the Global Positioning System (GPS) is not effective or requires too much time to achieve the required accuracy. EDM instruments are difficult to calibrate at most national measurement institutes as they are designed for large scale measurement and not for laboratory scales. The Natioanl Measurement Laboratory in Australia has a legal responsibility to provide traceabiltiy for EDM instruments and has developed two specialized facilities, a 650 m baseline and a 70 m optical bench, in order to establish EDM traceability to the Australian standard of length. The paper describes cyclic error and scale factor measurements on the baseline and on the optical bench. The conclusion is that the two techniques test different aspects of the EDM performance; short and long range performance. For the EDM instruments studied there are significant differences.

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as lens distortion, focal length, scale factor, pose, orientations, and distance. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1, 2, 3, 4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. The average scale factor tends to fluctuate with small variation and makes distance error decrease. Compared with classical methods that use stereo camera or two or three orthogonal planes, the proposed method is easy to use and flexible. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.

The Continuous Wavelet Transform (CWT) is an effective way to analyze nonstationary signals and to localize and characterize singularities. Fast algorithms have already been developed to compute the CWT at integer time points and dyadic or integer scales. We propose here a new method that is based on a B-spline expansion of both the signal and the analysis wavelet and that allows the CWT computation at arbitrary scales. Its complexity is O(N), where N represents the size of the input signal; in other words, the cost is independent of the scale factor. Moreover, the algorithm lends itself well to a parallel implementation.

This contribution focuses on the study and comparison of different design methods for designing phase-only diffractive optical elements (PDOEs) for different possible applications in laser beam shaping. Both binary and multilevel phase-only diffractive optical elements are considered, theoretically studied, and compared, using diffusive types of input objects. Especially, new results and approaches, concerning the iterative Fourier transform algorithm, are analyzed, implemented, and compared (the scale factor and the algorithm convergence characterization through the spectrum representation). The two important output design parameters, i.e. the signal-to-noise ratio and the diffraction efficiency characteristics are presented by means of evaluating their dependencies on, e.g. the number of iterations, the number of phase levels, and the signal-window position). Next, we concentrate on the design of Fresnel domain PDOEs, generalizing the classical IFTA scheme (both with a single and double focus) types of PDOEs. The application of the appropriate scale factors for each particular case is presented, and typical design results for both cases are shown. For practical realization, e-beam lithography technology is used, showing a good qualitative agreement with theoretical designs.

This paper investigates the problem of point-based registration under a similarity transformation. This is a transformation that consists of rotation, translation, and isotropic scaling. There are many applications for registration under a similarity transform. First, the medical applications that usually use rigid-body registration may in some cases be improved by using a scale factor to account for particular types of distortion (for example, drift in gradient strength in MR image volumes). Second, similarity transforms are often used in biometrics to analyze and compare different sets of data. It was shown by Gower in 1971 that the choice of scale factor is independent from the choice of rotation and translation. We use a well-known solution for the rotation and translation parts of the transformation, and concentrate on the problem of choosing the scale factor. We examine three different methods of scaling, one of which is a novel maximum likelihood approach. We derive the target registration error and show the bias for each method. We introduce two different models of fiducial localization error, and we show that for one error model, Gower's method of scaling to minimize the sum of squared distances between corresponding points is also the maximum likelihood solution. Under the other error model, however, maximum likelihood leads to a new method of scaling.

In this paper an adaptive template filtering method is described which can be used to increase the signal-to-noise ratio(SNR) and keep the important edge information of medical images. To date various filtering approaches are reported, most of them enhance SNR in different levels with loss of some useful information. We try to develop a robust algorithm. Unlike conventional filtering, where the template shape and coefficients are fixed, multiple templates are defined in the proposed algorithm. For each pixel, an optimal template is selected automatically depending on its neighbor pixels. Simulation and MRI image tests, both 2D and 3D, show that the new adaptive template filter provides higher SNR and sharper edges. Our method improved existing adaptive template filtering technique, corrected scale factor of threshold adjustment, extended it to 3D algorithm.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This contribution concentrates on a study and comparison of non- iterative design methods (error diffusion methods) based on a hardclip approach with iterative methods, namely iterative Fourier transform algorithm (IFTA), in designing binary phase-only diffractive optical elements (BPDOEs) for laser beam shaping. Two error diffusion methods as a non-iterative methods were considered, implemented and used for designing BPDOEs: the classical algorithm of error diffusion (ED) and the signal window minimum average error algorithm (SWMAE). Also, different schemes and approaches of IFTA algorithm were analyzed, implemented, and compared. The methods together with the simple hardclip method were analyzed for both diffusive and fan-out type objects: the signal-to-noise ratio and the diffraction efficiency dependencies on both the spatial-bandwidth product and on the signal-window position were obtained, enabling to determine the optimum design parameters and constraints within each method. As for the IFTA method, the role and a proper shape of the scale factor were analyzed, and a new way of characterization of the algorithm convergence was introduced, using the spectrum representation. The practical realization using e-beam lithography technology shows a good qualitative agreement with designed types of elements.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The Wafer-Induced-Shift (WIS) is the overlay measurement error due to the reflection trick of the metal film by Physical Vapor Deposition, specially sputtering. The WIS happens to the wide open type mark because this sputtering method can cause a non-symmetric edge deposition by the self-shadowing of mark depth. But the marks with a wide width and space, which are currently used in the industry, have not detected the WIS. It is the modification of overlay measurement mark that has to be primarily improved to solve this problem. So we suggest the new methodology using the overlay mark with the narrow space. The concept of this mark is to use the geometrical property of deposition and detect the optical contrast signal of the space-type mark instead of the edge contrast signal of wide bar-type mark. This will reduce the non-symmetric deposition property by the self-shadowing. In this paper, we conformed the WIS using the overlay errors after and before etching film, and reported the effectiveness of our new mark by using the sputtered Pt film being one of the electrodes of BST capacitor. Several marks with a space 0.2 micrometer up to 0.5 micrometer were examined for the various thicknesses of the film by comparing the overlay measuring error between the standard mark and the new mark, and correlating the degree of the metal filing into the narrow space of overlay mark with the wafer scale factor. From the experimental results, we can find that the major component of WIS is the wafer magnification factor, and the new mark had a good feasibility for the WIS and might be called the WIS-free mark. Additionally we will discuss more details of our experimental results.

We demonstrate a method of obtaining scale invariance detection using a white light optical correlator. We are able to detect different scaled versions of the target in the same scene up to a magnification factor equal to 2. Each scale factor is codified in a different wavelength so each scaled version of the target is detected with a correlation peak of different wavelength. Experimental results demonstrate the proposed technique and show the utility of the method here introduced.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Besides the scale factor that distinguishes the various spices fundamentally biological muscles changes little between species indicating a highly optimized system, Electroactive polymer actuators offer the closest resemblance to biological muscles however beside the large actuation displacement these materials are falling short with regards to the actuation force. As improved materials emerging it is becoming necessary to address key issues such as the need for effective electromechanical modeling and guiding parameters in scaling the actuators. In this paper, we will review the scaling laws for three major actuation mechanisms that are of relevance to micro electromechanical systems: electrostatic actuation, magnetic actuation, thermal bimetallic actuation, and piezoelectric actuation.

This paper presents an approach to automatically register IR and millimeter wave images for concealed weapons detection application. The distortion between the two images is assumed to be a rigid body transformation and we assume that the scale factor can be calculated from the sensor parameters and the ratio of the two distances from the object to the imagers. Therefore, the pose parameters that need to be found are x-displacement and y-displacement only. Our registration procedure involves image segmentation, binary correlation and some other image processing algorithms. Experimental results indicate that the automatic registration procedure performs fairly well.

In case of robot vision, most important problem is the processing speed of acquiring and analyzing images are less than the speed of execution of the robot. In an actual robot color vision system, it is considered that the system should be processed at real time. We guessed this problem might be solved using by the bicolor analysis technique. We have been testing a system which we hope will give us insight to the properties of bicolor vision. The experiment is used the red channel of a color CCD camera and an image from a monochromatic camera to duplicate McCann's theory. To mix the two signals together, the mono image is copied into each of the red, green and blue memory banks of the image processing board and then added the red image to the red bank. On the contrary, pure color images, red, green and blue components are obtained from the original bicolor images in the novel color system after the scaling factor is added to each RGB image. Our search for a bicolor robot vision system was entirely successful.