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Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Monocular stereo vision has excellent application prospects in the field of microrobots. On the basis of the geometric model of bifocal imaging, this paper proposes a monocular depth perception method by liquid zoom imaging. Firstly, the configuration of a monocular liquid vision system for depth measurement is presented, and the working mechanism of the system is analyzed through theoretical derivation. Then, to eliminate the influence of optical axis drift induced by the liquid gravity factor on the measurement results, the target image area is used as the calculation feature instead of the image vector length. A target area calculation method based on chain code classification and strip segmentation is proposed. Furthermore, in response to the fluctuation problem of liquid lens focal power caused by factors such as temperature and object distance, a dynamic focal length model of the liquid zoom imaging system is constructed after precise calibration of the focal power function. Finally, a testing experiment is designed to validate the proposed method. The experimental results show that the average error of depth perception methods is 4.30%, and its measurement time is only on the millisecond scale. Meanwhile, the proposed method has good generalization performance. [ABSTRACT FROM AUTHOR]

Indonesia needs bathymetry information for diverse applications as a maritime country. There are various methods of determining the water depth for bathymetry. The advancement of satellite imagery data has led to the increasing use of remote sensing data for depth measurements. With satellite imaging, wide area coverage can be achieved in a relatively short time, making depth data acquisition more cost-effective. SAR (Synthetic Aperture Radar) imagery is an active remote sensing technology developed to estimate depth data known as the SAR Bathymetry method. This method is still not widely applied, especially in Indonesia, even though it has considerable potential with cloud-free imageries, where it becomes a severe problem in tropical countries when using optical imagery. Therefore, this paper will discuss algorithms and techniques for depth data estimation using SAR Bathymetry and their possible implementation in Indonesia. The optimum depth, SAR image recommendation, and conditions required to apply this method will also be discussed.

Monocular vision-based 3D scene understanding has been an integral part of many machine vision applications. Always, the objective is to measure the depth using a single RGB camera, which is at par with the depth cameras. In this regard, monocular vision-guided autonomous navigation of robots is rapidly gaining popularity among the research community. We propose an effective monocular vision-assisted method to measure the depth of an Unmanned Aerial Vehicle (UAV) from an impending frontal obstacle. This is followed by collision-free navigation in unknown GPS-denied environments. Our approach deals upon the fundamental principle of perspective vision that the size of an object relative to its field of view(FoV) increases as the center of projection moves closer towards the object. Our contribution involves modeling the depth followed by its realization through scale-invariant SURF features. Noisy depth measurements arising due to external wind, or the turbulence in the UAV, are rectified by employing a constant velocity-based Kalman filter model. Necessary control commands are then designed based on the rectified depth value to avoid the obstacle before collision. Rigorous experiments with SURF scale-invariant features reveal an overall accuracy of 88.6% with varying obstacles, in both indoor and outdoor environments. [ABSTRACT FROM AUTHOR]

How to simultaneously obtain the depth, edge, and other light information of the scene to accurately perceive the physical world is an important issue for imaging systems. However, such tasks usually require bulky optical components and active illumination methods. Here, we design and experimentally validate a single geometric metasurface that can achieve depth measurement or edge detection under incoherent or coherent light respectively. Double helix point source function is utilized, and three verification experiments are carried out, including double-helix beam calibration, 2D object and 3D object detection, respectively. Additionally, two-dimensional edge detection can also be achieved. This compact imaging system can enable new applications in various fields, from machine vision to microscopy.

Real-time access to the physical parameters of a liquid such as temperature, refractive index, and depth in a vessel could contribute to preserving the quality of the liquid. In this study, the optoelectronic oscillator-based measurement of these physical parameters is discussed. The refractive index, the temperature, and the depth of the liquid are translated into a variation in the oscillation frequency of the optoelectronic oscillators. For the temperature and refractive index, the phase-shifted fiber Bragg grating immersed in the liquid acts as a sensor. Contrariwise, the depth measurement of the liquid is achieved through the round-trip flow of the light in the vessel. Using appropriate values of the system parameters, the theoretical sensitivities for the temperature and depth were reported as 283 MHz/°C and 421.94 MHz/cm , respectively. It is also noticed that when tuning the cubic-nonlinear parameter, the cubic-nonlinear optoelectronic oscillator significantly increases the measurement sensitivity. [ABSTRACT FROM AUTHOR]

Monocular stereo vision has excellent application prospects in the field of microrobots. On the basis of the geometric model of bifocal imaging, this paper proposes a monocular depth perception method by liquid zoom imaging. Firstly, the configuration of a monocular liquid vision system for depth measurement is presented, and the working mechanism of the system is analyzed through theoretical derivation. Then, to eliminate the influence of optical axis drift induced by the liquid gravity factor on the measurement results, the target image area is used as the calculation feature instead of the image vector length. A target area calculation method based on chain code classification and strip segmentation is proposed. Furthermore, in response to the fluctuation problem of liquid lens focal power caused by factors such as temperature and object distance, a dynamic focal length model of the liquid zoom imaging system is constructed after precise calibration of the focal power function. Finally, a testing experiment is designed to validate the proposed method. The experimental results show that the average error of depth perception methods is 4.30%, and its measurement time is only on the millisecond scale. Meanwhile, the proposed method has good generalization performance.

A camera-based single-image sensor is presented, that is able to measure the distance of one or multiple object points (light emitters). The sensor consists of a camera, whose lens is upgraded with a diffractive optical element (DOE). It fulfils two tasks: adding a vortex point spread function (PSF) and replication of the vortex PSFs to a predefined pattern of K spots. Both, shape and rotation of the vortex PSF is sensitive to defocus. The sensor concept is presented and its capabilities evaluated both on axis and off-axis. The achieved standard deviation of the error ranges between 8.5 μm (on-axis) and 3.5 μm (off-axis) within a measurement range of 20 mm. However, as soon as calibration and measurement position no longer match, the accuracy is limited. An analysis of the effects responsible for this are also part of the publication. [ABSTRACT FROM AUTHOR]

In developing countries, stray animals can be frequently encountered on the roads, pathways, campuses, and other places. Due to this, the visually impaired (VI) are at more risk than the sighted ones. To gain more security and safety, they need a solution to deal with their problem. This experimentation aims to develop a hardware–software integrated solution that can detect stray animals. Along with the detection, the solution should also provide the distance of those objects from the user and alert them if it is getting closer. To put this experiment together, Jetson NANO and ZED mini camera have been chosen for processing and image capturing to make the solution mobile and accurate as they are leading hardware devices. A novel approach involving quantization and anchor-optimization has been proposed using Single-Shot Detector (SSD) Resnet 50 FPN as the base model. The model has been compressed by quantization to reduce the inference time, and anchor optimization has been done to compensate for the accuracy loss faced during quantization. We have performed experimentation by training the original model, anchor-optimized model, and quantization plus anchor-optimized model using batch sizes 64 and 8. This experimentation has been done to understand the effect of anchor-optimization and quantization on the base model and the effect of the batch size used for training on different model versions. The performance of all the models with applied quantization and anchor-optimization for both batch sizes 64 and 8 has been noted in mAP. The mAP of the quantized plus anchor-optimized model trained using batch size 64 was the highest, i.e. 93.5%. It can also be concluded that we can achieve the light-weight model with the best performance by balancing quantization and anchor-optimization to make it suitable for an edge device using batch size 64. [ABSTRACT FROM AUTHOR]

Microstructures are widely used in the manufacture of functional surfaces. An optical-based super-resolution, non-invasive method is preferred for the inspection of surfaces with massive microstructures. The structured illumination microscopy (SIM) uses standing-wave illumination to reach optical super-resolution. Recently, coherent SIM is being studied. It can obtain not only the super-resolved intensity distribution but also the phase and amplitude distribution of the sample surface beyond the diffraction limit. By analysis of the phase-depth dependency, the depth measurement for microgroove structures with coherent SIM is expected. FDTD analysis is applied for observing the near-field response of microgroove under the standing-wave illumination. The near-field phase shows depth dependency in this analysis. Moreover, the effects from microgroove width, the incident angle, and the relative position between the standing-wave peak and center of the microgroove are investigated. It is found the near-field phase change can measure depth until 200 nm (aspect ratio 1) with an error of up to 20.4 nm in the case that the microgroove width is smaller than half of the wavelength. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Microstructures are widely used in the manufacture of functional surfaces. An optical-based in-process and non-invasive method is preferred for the depth measurement of the fine microgroove structure. A dark-field method is proposed using the features of polarization based on the waveguide theory. According to the numerical simulation based on the FDTD method and Fourier optics, the proposed method allows depth measurement for fine microgroove having an aperture size of less than several hundred nanometers with an aspect ratio (width/depth) of larger than one, even under the far-field measurement.

Measuring the distance is one of the main objectives for sensor development. In this article, we present a new sensor system design for depth recovery. It is based on stereopsis with the integrated rotation of an image sensor. Different from conventional stereo vision systems with multiple cameras, the proposed rotational stereo configuration is built upon a single imaging device. By directing its lateral motion with a circular constraint, the visual parallax is generated from multiple viewpoints. The image pairs captured with the integrated sensor rotation are used for the correspondence matching and disparity computation. Moreover, a variation of multiple-baseline stereo with multiple base-angle implementation is proposed. It provides a flexible baseline setting to improve the depth measurement accuracy. The geometric formulation and computational algorithm are derived and developed. In the experiments, a prototype range sensing device is constructed. The results obtained from the real scene environment have demonstrated the feasibility of the proposed depth measurement approach. [ABSTRACT FROM AUTHOR]

Aim of the study Recently, the use of acoustic Doppler current profilers (ADCP) gains in popularity. Considering the use of various equipment, a question arises whether there are any differences in measuring with ADCP that works at different frequencies. The aim of this study was to compare and evaluate three ADCPs operating at different frequencies: 2,000 kHz, 1,500 kHz, and 600 kHz under field conditions. Material and methods Following parameters were applied for a transverse section of 100 m in width and 7 m in depth: (1) components of velocity flow, (2) depth, (3) transverse distance among vectors, (4) total distance and (5) geographic position of each vector. Results and conclusions The results showed that velocity magnitudes were low in margin areas, while high in the center. In comparison with other devices the 2,000 kHz ADCP keeps a homogeneous velocity distribution up to 5.0 m in depth. Also, the statistical and graphic analysis demonstrated that flow measurements did not differ by more than 5%. Nevertheless, the review of velocities showed significant differences between ADCPs. High frequency means more detailed data, but less deep range, particularity in zones with upper sediments concentration. Low frequency means less detailed data, but deeper range. Furthermore, our findings suggest that measurements performed in rivers provide results, which sometimes are entirely different from results obtained in laboratory.

With the continuous development of computer vision technology and the continuous upgrading of digital imaging equipment, image depth measurement method is widely used in the fields of intelligent robotics, traffic assistance, three-dimensional modeling and three dimensional video production. The following are the drawbacks of the traditional depth information measurement method: the operation is complex, the cost is high, and the measuring equipment occupies a large space and the load. In this paper, based on the Harris-SIFT corner detection algorithm, a technique is proposed to measure the absolute depth information of the object in the image using monocular vision. First of all, after the monocular camera is used to obtain the image of the target object, the image segmentation algorithm based on the LBF model is used to preprocess the image. Then, Harris algorithm in multi-scale space and SFIT algorithm to reconstruct feature descriptors are used to extract feature information in the image. Finally, by comparing the feature information between image groups, the depth information of target object is calculated by using the formula of convex hull principle and camera imaging principle. The test platform is applied to carry out measurement tests for different depth measurement methods, and the actual depth data and measurement data of the target object are compared, so as to evaluate the accuracy of the measurement method. The comparison results show that the error rate between the actual distance and the measured distance is less than 3.5%, which can accurately measure the absolute depth of the object in static and short distance, and is superior to other measurement methods. [ABSTRACT FROM AUTHOR]

The alternating current potential drop technique has been widely used to measure subsurface cracks in metal structures. However, the application of the technique to random cracks has, to date, been limited. By using a multidirectional alternating current potential drop technique, the angle between crack and exciting electrode wire changes from 0° – 90° to 67.5° – 90°, which considerably expanded the ranges of detection. Simulation and experiment results showed that this technique can accurately measure the depth of random cracks.

Today's methods for the inspection of the position of weld seams in glass, which has a decisive effect on the strength and thus on the quality of the permanent bond, are costly and often carried out manually in a destructive manner. The present paper proposes the application of optical coherence tomography to determine the position of the weld seam by evaluation of the signals caused by the voids within weld seams. Blind welds of fused silica and alkali-aluminosilicate glass were investigated, and a method for data evaluation is presented. The method is predominantly suitable for glass that exhibits the formation of distinct voids during welding and provides an approach for online monitoring and control of glass welding processes. [ABSTRACT FROM AUTHOR]

A radar system has been developed to predict global warming by measuring ice-shelf thicknesses. This system uses a frequencymodulated continuous-wave(FMCW) waveform and phase-sensitive method through the so-called Vernier-like process, which measures the target range by adding the fine range from the phase information to the rough range from the frequency. However, the continuous waves require a large dynamic range of the receiver because short-range and long-range reflection signals are received simultaneously. To improve this, we propose a frequency-modulated interrupted continuous wave(FMICW) method and demonstrate its performance through simulation. Although the proposed method reduces the signal-to-noise ratio(SNR) based on the same peak power, the gain can be adjusted according to the range, and the minimum detection range can be controlled. [ABSTRACT FROM AUTHOR]

Precision laser micromachining plays an important role in the biomedical, electronics, and material processing industries. During laser drilling, precision depth detection with micrometer-level resolution is required, particularly with blind-hole or heterogeneous structures. We present an optical detection system utilizing an optical confocal structure, experimentally confirmed to achieve a >95% accuracy for micron-diameter holes that are tens-of-microns deep. This system can be easily integrated into commercial laser micromachining processes, and can be employed in laser drilling and three-dimensional active-feedback laser printing.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver–pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver–pickup, also termed as transmitter–receiver (T-R) sensor is designed with a small mean radius of 1 mm. In addition, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution, with a limit of 0.2 μm and selected as 0.25 mm. Experiments were conducted for imaging of an aluminium sheet with seven machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10% for tilt angles up to 60 degrees.

Highlights • We present a method to obtain the weld seam depth with high accuracy, with an error of less than 5%. • We use a statistical approach to subdivide depth measurement in significant depths signals and noise. • The method removes the need to adapt the filtering parameters to the process and measurement conditions. The same parameters can be used for depth measurements of welding steel and aluminum. Abstract A statistical filtering method to determine the depth of laser-welded seams from signals recorded by means of optical coherence tomography (OCT) is proposed and discussed. The measured data points are initially classified into noise and significant data by means of a noise probability, which was defined based on the normalized Poisson distribution. A percentile filter is then applied to the significant data to obtain the depth of the weld seam. It is shown that the depth determined by this approach corresponds to the real seam depth, as obtained from longitudinal sections, to within an average error of less than 5%. The method can be applied to different laser welding situations without having to adjust the filter parameters. [ABSTRACT FROM AUTHOR]

This paper presents the effects of aperture diameter on image blur of complementary metal–oxide–semiconductor (CMOS) image sensor with pixel apertures for depth extraction. In a conventional camera system, the aperture is located at the camera lens. However, in the proposed camera system, the aperture is located on the photodiode. The patterns in the pixel array of the fabricated CIS are composed of blue, red, and white pixels, as well as pixel apertures. The pixel apertures are formed by a metal pattern in the white pixels and designed using a metal layer in the CIS process. The focused and defocused images are simultaneously obtained using white pixels with and without the pixel apertures. The focused image can be used as a reference image to extract depth information for 3-D imaging. The sensor was designed and fabricated using the 0.11- $\mu \text{m}$ CIS process. The image blur as a function of the aperture diameter was measured using the fabricated sensor. In addition, the effects of the $F$ -number of the camera lens, which is defined as the ratio of focal length to the diameter of the camera lens, and variation in the output of the CIS with the angle of incidence were investigated. [ABSTRACT FROM AUTHOR]

Time-of-Flight (ToF) cameras are nowadays commonly used for depth measurements and are useful in applications, such as robotic navigation, gaming, and others. The depth measurements by the ToF camera are influenced by the systematic errors of the camera and the nonsystematic errors of the environment. This paper presents a novel method for reduction of depth measurement error using polarization state of the reflected light. Using polarization state of the reflected light, the nonsystematic errors introduced due to multipath interference, material properties, and color of the target object reduces, which reduces the depth errors. The idea is tested using SR-4000 3-D sensor and a linear polarizer in front of it. The transmission angle of the linear polarizer is varied for a fixed object distance from the camera. The depth error has a sinusoidal variation with clear maxima and minima. It is observed that the depth error is minimum when the polarization angle is equal to the ToF phase shift. The experimental results show a maximum of 87% reduction in depth error at 3000 mm distance using polarization angle equal to ToF phase shift. The reduction in the nonsystematic error in the ToF-based distance measurements using polarization of the reflected light will enable new applications, such as diffuser imaging, detection of transparent objects, and among others. [ABSTRACT FROM AUTHOR]

Highlights • A new C-type grating structure was proposed for simultaneous measurement. • Because wedge-shaped defects got introduce, high birefringence was excited. • Thermo sensitive materials filled in micro pores to improve the performance. • Established a mathematical model of birefringence effect in C-type structure. • Analyzed stress distribution in all directions under two disturbances. Abstract A new C-type micro-structured grating structure was proposed for simultaneous measurement of depth and temperature in seawater. Because wedge-shaped defects got introduce, high birefringence was excited at fiber core of grating. Thermo sensitive materials filled in micro pores to improve the sensitivity of temperature. Then we established a mathematical model of birefringence effect in C-type structure. This work analyzed stress distribution in all directions under two disturbances. In pressure and temperature environment, reflection peaks in two-polarization states separated with a large offset. Two characteristic parameters: λ B, y − λ B, x , λ B, y + λ B, x were proposed for corresponding measurement. Structural parameters got optimize for better performance. Calculated output signals had high sensitivity and linearity under pressure range of 0–10 MPa and temperature range of 0–40 °C. λ B, y − λ B, x mainly responded to pressure, which got sensitivity −1.709 nm/MPa. While temperature mainly influenced λ B, y + λ B, x and the obtained temperature sensitivity was 1.054 nm/°C. This structure would have a great potential application due to the mature demodulation technique of grating signal. [ABSTRACT FROM AUTHOR]

The Kinect sensor has been widely used in different applications such as rehabilitation and gait analysis. Whilst Kinect v2 was released with several improvements over its predecessor, it still incorporates depth-map intrinsic inaccuracies. This results in inconsistencies in skeletal-data acquisition, especially in joint localisation and distance-to-ground tracking with respect to the Kinect's 3-D Cartesian coordinate reference point. This research proposes a correction technique based on the two-point linear equation derived from the information gathered from different subjects' skeletal data and data regression analysis to compensate the inaccuracies in joint-to-ground data collection. The research also proposes a new footsteps detection method based on skeletal data and plane detection techniques that calculates a footstep by using the ankle's Euclidean distance from the floor, regardless of the subject's distance from the camera. The results show that after the correction technique was applied, data acquisition proved to be consistent and more accurate within a distance range of 1.6-2.9 m from the Kinect camera, regardless of the subject's location to the camera's reference point. Moreover, the inconsistency of joint data read by the Kinect was reduced from 25.69% to 5.25% and the footsteps detection accuracy increased from 42.85% to 79.76% on average for both legs. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Polonorum. Formatio Circumiectus is the property of Wydawnictwo Uniwersytetu Rolniczego im. Hugona Kollataja w Krakowie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, laser processing equipment was used to drill aluminum alloy materials and with different auxiliary mechanisms, the deformation around the holes after processing was observed. The experimental results show that, due to the high temperature generated during laser processing, a large thermal gradient causes thermal stress to be introduced into the test piece and outward expansion deformation occurs. In this study, the digital image correlation and residual stress detection methods were applied. Based on the correlation between the drilled hole depth and the hole deformation, the hole depth of the laser processing was estimated. The average coefficient of determination for all auxiliary mechanisms is 0.82. The experimental results confirm that the digital image correlation method can be used to estimate the hole depth of laser processing.

Shape-from-focus depth measurement is widely used in equipment manufacturing, biomedicine, heritage conservation, engineering measurement, etc. However, the acquisition of multi-focus image sequence is not very flexible and time-consuming in conventional shape from focus. Here, a novel depth measurement from shape from focus method based on ultrafast optical axial scanning was proposed. An electronically tunable lens was used to achieve high-speed focus shift, by synchronizing a CCD with the electronically tunable lens, multi-focus image sequence can be acquired at high speed (up to 2.5 ms). The focusing area of each multi-focus image was extracted by the energy of image gradient operator. Finally, the motionless depth measurement can be achieved. A tilted marker pen was used to test the performance of the depth measurement, the results show that the depth resolution of the proposed method is measured to be ∼ 3.2 cm in a depth range of ∼ 24 cm. The feasibility of the proposed method was verified using misplaced portrait sculptures. This method will further expand the application of depth measurement from shape from focus in human–computer interaction, 3D shape measurement, and augmented reality. [ABSTRACT FROM AUTHOR]

Several three-dimensional scanning methods have been developed and improved over the past 40 years. The peculiarities of each technique, associated with the computational advances of the period, allowed the increasing application and diffusion of the technology in several sectors, among them those related to metrology in ballistics and the testing of protective materials. The specific goal of such ballistic tests is to estimate the depth of indentation caused by projectiles. In particular, this study presents a comparative analysis between two three-dimensional optical scanning methods, taking into account the same object of interest. The comparative analysis was based on reference planes detected by Random Sample Consensus methodology in each cloud. By comparing the results of the different techniques, it was found for this case that three-dimensional reconstruction by stereo images estimated values closer to the real ones in comparison to those estimated by the structured light scanner, mainly due to the fact that, for three-dimensional reconstruction, the image acquisition was conducted statically.

Single-shot 3D imaging and shape reconstruction has seen a surge of interest due to the ever-increasing evolution in sensing technologies. In this paper, a robust single-shot 3D shape reconstruction technique integrating the structured light technique with the deep convolutional neural networks (CNNs) is proposed. The input of the technique is a single fringe-pattern image, and the output is the corresponding depth map for 3D shape reconstruction. The essential training and validation datasets with high-quality 3D ground-truth labels are prepared by using a multi-frequency fringe projection profilometry technique. Unlike the conventional 3D shape reconstruction methods which involve complex algorithms and intensive computation to determine phase distributions or pixel disparities as well as depth map, the proposed approach uses an end-to-end network architecture to directly carry out the transformation of a 2D image to its corresponding 3D depth map without extra processing. In the approach, three CNN-based models are adopted for comparison. Furthermore, an accurate structured-light-based 3D imaging dataset used in this paper is made publicly available. Experiments have been conducted to demonstrate the validity and robustness of the proposed technique. It is capable of satisfying various 3D shape reconstruction demands in scientific research and engineering applications.

This paper studies the control performance of visual servoing system under the planar camera and RGB-D cameras, the contribution of this paper is through rapid identification of target RGB-D images and precise measurement of depth direction to strengthen the performance indicators of visual servoing system such as real time and accuracy, etc. Firstly, color images acquired by the RGB-D camera are segmented based on optimized normalized cuts. Next, the gray scale is restored according to the histogram feature of the target image. Then, the obtained 2D graphics depth information and the enhanced gray image information are distort merged to complete the target pose estimation based on the Hausdorff distance, and the current image pose is matched with the target image pose. The end angle and the speed of the robot are calculated to complete a control cycle and the process is iterated until the servo task is completed. Finally, the performance index of this control system based on proposed algorithm is tested about accuracy, real-time under position-based visual servoing system. The results demonstrate and validate that the RGB-D image processing algorithm proposed in this paper has the performance in the above aspects of the visual servoing system.

Over the past ten years, diabetes has rapidly become more prevalent in all age demographics and especially in children. Improved dietary assessment techniques are necessary for epidemiological studies that investigate the relationship between diet and disease. Current nutritional research is hindered by the low accuracy of traditional dietary intake estimation methods used for portion size assessment. This paper presents the development and validation of a novel instrumentation system for measuring accurate dietary intake for diabetic patients. This instrument uses a mobile Structured Light System (SLS), which measures the food volume and portion size of a patient’s diet in daily living conditions. The SLS allows for the accurate determination of the volume and portion size of a scanned food item. Once the volume of a food item is calculated, the nutritional content of the item can be estimated using existing nutritional databases. The system design includes a volume estimation algorithm and a hardware add-on that consists of a laser module and a diffraction lens. The experimental results demonstrate an improvement of around 40% in the accuracy of the volume or portion size measurement when compared to manual calculation. The limitations and shortcomings of the system are discussed in this manuscript.

The depth measurement error of bionic eyes consisting of two active cameras is derived by considering the eyes' rotation angle errors and image feature extraction errors. The effect factors of the depth measurement are obtained from the calculation formula of depth error. Based on the analysis of these effect factors, some effective guidelines for bionic eyes are proposed to reduce the measurement errors. The guidelines suggest keeping long baseline, observing the target as nearly as possible, controlling two active cameras with the same angular velocity and keeping the target on Zw axis if possible. The simulation experiments and practical experiments in bionic eyes platform validate the effectiveness of the proposed guidelines. [ABSTRACT FROM AUTHOR]

Recovering depth information of objects from two-dimensional images is one of the very important and basic problems in the field of computer vision. In view of the shortcomings of existing methods of depth estimation, a novel approach based on SIFT (the Scale Invariant Feature Transform) is presented in this paper. The approach can estimate the depths of objects in two images which are captured by an un-calibrated ordinary monocular camera. In this approach, above all, the first image is captured. All of the camera parameters remain unchanged, and the second image is acquired after moving the camera a distance d along the optical axis. Then image segmentation and SIFT feature extraction are implemented on the two images separately, and objects in the images are matched. Lastly, an object's depth can be computed by the lengths of a pair of straight line segments. In order to ensure that the most appropriate pair of straight line segments are chosen, and also reduce computation, convex hull theory and knowledge of triangle similarity are employed. The experimental results show our approach is effective and practical. [ABSTRACT FROM AUTHOR]

This paper presents a method for processing the data obtained from Microsoft Kinect device fitted with Nyko Zoom attachment. This system is used to obtain the dimensions of items placed in the workspace of prototype glue spraying machine. The presented data acquisition method allows to describe the shape of the surface and accurately determine the item position. The paper deals with processing of information on the registered object changed by the used attachment. The lens allowed to increase the angle of view of the Kinect device while reducing the minimum working distance. Included in the working method of correction is the solution to the problem presented to the constant exposure of the background. The described solution is used as a subsystem for the identification of seats and can be used in designing a subsystem to calculate the trajectory of the spraying head. [ABSTRACT FROM AUTHOR]

Monocular depth measurement is an important fundamental technology in machine vision with a wide range of application scenarios, while traditional monocular focus measurement systems have deficiencies such as large size and slow response time. Low measurement accuracy of existing monocular measurement algorithms and can only measure for specific targets. Based on this, A liquid bionic vision system is proposed and a monocular depth measurement model is developed, the structural parameters are optimized using the NSGA-II algorithm. After calibrating the liquid lens, a neural network-based monocular intelligent depth measurement method is proposed, expressing the relationship between the liquid lens control current and the target depth. The experimental results show that the proposed method and the designed system perform well in terms of measurement accuracy, stability and applicability, with a relative error of less than 1.11 % within a measurement range of 1 m and single measurement time does not exceed 410 ms. • A monocular depth measurement model based on a liquid vision system is proposed. • The liquid bionic vision system was optimally designed using the NSGA-II algorithm. • A neural network-based intelligent depth measurement method was designed. • The proposed measurement method has excellent accuracy and generalization ability. [ABSTRACT FROM AUTHOR]

To measure the depth and diameter of through silicon vias simultaneously, a novel method based on spectral-domain interferometer and confocal microscope is proposed and realized. Most parts of the measurement system are constructed with optical fiber components for flexible configuration and easy alignment. According to the measurement results and performance evaluation, the mean values of the diameter and depth were 6.07 μm and 48.255 μm with the expanded uncertainties of 0.20 μm (k\,= \,\text2 ) and 37 nm (k\,= \,\text2 ), respectively. [ABSTRACT FROM PUBLISHER]

Abstract Measurement the depth of ion implantation is considered to be one of the important subject in physics , which has been employed by using SIMS and RBS methods. In this research Electron spectroscopy of chemical Analysis (ESCA) technique has been used to determine the depth of indium ion implantion in P-N Junction silicon semiconductor sample , which has been prepared by using pulse dense plasma focus . Such determination was depend on the chemical shift of the silicon spectrum. The prepared sample was scraped until the above noted chemical shift was disappeared. From this technique the depth of indium doped in the silicon sample was found to be about 450 A° .