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This paper describes signal processing in the encrypteddomain, i.e., that after encryption but before decryption. In this framework, signal processing operations can be directly applied to encrypted signals without decrypting of encrypted signals, whereas the ordinary framework encrypts signals for transmission and/or storing but it decrypts them before signal processing operations are applied to. The described framework befits contemporary cloud computing in which not only transmission but also storing and processing are done in the public Internet. Addition to brief survey, two tangible application scenarios are also demonstrated in this paper where a new signal processing algorithm is introduced each.

A feasible pavement crack detection system plays an important role in evaluating the road condition and providing the necessary road maintenance. In this paper, a back propagation neural network (BPNN) is used to recognize pavement cracks from images. To improve the recognition accuracy of the BPNN, a complete framework of image processing is proposed including image preprocessing and crack information extraction. In this framework, the redundant image information is reduced as much as possible and two sets of feature parameters are constructed to classify the crack images. Then a BPNN is adopted to distinguish pavement images between linear and alligator cracks to acquire high recognition accuracy. Besides, the linear cracks can be further classified into transversal and longitudinal cracks according to the direction angle. Finally, the proposed method is evaluated on the data of 400 pavement images obtained by the Automatic Road Analyzer (ARAN) in Northern China and the results show that the proposed method seems to be a powerful tool for pavement crack recognition. The rates of correct classification for alligator, transversal and longitudinal cracks are 97.5%, 100% and 88.0%, respectively. Compared to some previous studies, the method proposed in this paper is effective for all three kinds of cracks and the results are also acceptable for engineering application.

This paper presents an innovative method of face detection by supplementing dynamic time warping algorithm with proposed image processing strategy and weighting scheme. Using our proposed approach overcomes some of the shortcomings in applying dynamic time warping for face detection, hence improving the performance and detection accuracy. The results presented and discussed in this paper show the efficacy of our approach in using DTW for face detection. Ill. 16, bibl. 16, tabl. 1 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.108.2.154

In these recent years, Compressive Sensing (CS) is becoming an attractive topic in the field of Information Theory. It is widely used in several area including networking, image processing and digital camera. In particular, image reconstruction based on small number of measured components is known as the most useful application. In this paper, SL0 algorithm is specially used for the reconstruction process. It significantly decrease the processing time by utilizing a matrix in which the number of row is much smaller than number of column. Therefore, SL0 is known as one of the fastest and most accurate algorithm in CS. However due to ill-posed condition, if the prior information of the original image is undetermined, the reconstruction procedure of SL0 is much affected by the noise. Unfortunately, the investigation for solving this SL0 ill-posed condition is very limited therefore SL0 is not widely applied in many application. Consequently, this paper proposes a novel regularization technique for SL0 algorithm in the frequency domain. In order to reduce and constraint the space of reconstructed image, the frequency domain Tikhonov regularization technique is employed. It is shown that the quality of the reconstructed image is much better compared to the traditional algorithm under the noisy environment. The experimental result is exclusively simulated for 3 images: Lena, Sussie and Cameraman under both Gaussian and Non-Gaussian noise models (such as AWGN, Poisson noise, Salt & Pepper noise and Speckle noise) at different noise powers.

The spatial and spectral luminance properties of a cloud's surface are being studied to gather more information about the microphysical processes occurring within the cloud. A real-time, field-implementable image processing system has been developed by the authors to sense and display this luminance information, and is described in this paper. Applications, including the investigation of “crown flash” phenomena, are described.

This paper describes the fabrication and demonstration of a real-time incoherent-to-coherent optical converter having applications in image processing systems. Briefly, it utilizes the photoconductivity effect in the single-crystalline electrooptic material, Bi 12 SiO 20 to spatially modulate its electrical polarization. An optically absorbed write-in image is stored as an image wise polarization pattern in the device. Readout is accomplished electrooptically by means of the subsequent phase retardation that a polarized beam of coherent light undergoes in passing through the Bi 12 SiO 20 . An operating mode for achieving continuous image conversion with high-speed recyclability is described. The following performance characteristics have been demonstrated : write-in intensity of 300 µW/cm2at 400 nm yielded a contrast ratio of 50:1 after 40-ms exposure. When the converter was operated at a frame rate of 10/s, a sampled read-out contrast ratio of greater than 1000:1 was achieved. Resolution in excess of 80 1p/mm has been recorded and read out. The crystal growing and device fabrication methods by which 1-square-in converters have been built and operated are described. Results achieved in using this device to Fourier transform images are also presented.

This paper describes an algorithm for the approximate solution of vector Toeplitz systems via an iterative-improvement method. The algorithm exploits the special structure of Toeplitz matrices, namely, their similarity to vector circulants, and is particularly well suited for solving large systems. Sufficient convergence conditions and concrete error bounds for the iteration are presented along with an application of the routine to a problem in the design of planar digital filters for image processing.

Recursive restoration of two-dimensional noisy images gives dimensionality problems leading to large storage and computation time requirements on a digital computer. This paper shows a two-dimensional second-order Markov process representation can be used for fast recursive restoration of images with small storage requirements. Advantages of this method over existing techniques are illustrated by means of examples.

This paper describes various forms of line drawing representation, compares different schemes of quantization, and reviews the manner in which a line drawing can be extracted from a tracing or a photographic image. The subjective aspects of a line drawing are examined. Different encoding schemes are compared, with emphasis on the so-called chain code which is convenient for highly irregular line drawings. The properties of chain-coded line drawings are derived, and algorithms are developed for analyzing line drawings to determine various geometric features. Procedures are described for rotating, expanding, and smoothing line structures, and for establishing the degree of similarity between two contours by a correlation technique. Three applications are described in detail: automatic assembly of jigsaw puzzles, map matching, and optimum two-dimensional template layout

In the formation of an optical image, each surface element of the object gives rise to a more or less blurred distribution in the image surface, of total brightness proportional to that of the object element. The image is the sum of these distributions in the appropriate sense: when the object is coherently lit, the image is built up by adding their complex amplitudes; when the object elements are regarded as incoherent it is the intensities which are added. In both cases the image can be expressed as the convolution of the object with a spread function which characterizes the optical system. In systems for which the spread function does not change appreciably from one part of the field to another, the Fourier transform of the image is obtained to a sufficient approximation on multiplying the Fourier transform of the object with that of the spread function. More generally, this holds for any part of the field of a non-isoplanatic system over which the changes in the form of the spread function are small enough to be disregarded; we call such an area an 'isoplanatism-patch'. Working over such an area, an optical system can be regarded as a linear filter in which the Fourier components of the object reappear in the image multiplied by 'transmission factors'. These factors, first considered by Duffieux, depend on the aperture and aberrations of the system, and in Section 2 they are evaluated in terms of an ikonal function. The qualities required of an optical image are so varied that an assessment valid over the whole range of practical applications seems out of the question. Two extreme cases are considered in the present paper. In the first of these it is assumed that the aim of an optical design is to produce an image which is directly similar to the object. This is appropriate when no process of image interpretation or reconstruction is envisaged. In the second case, the aim is to produce an image containing the greatest possible amount of information about the object, without regard to the complexity of the interpretation processes which may be needed to extract it. For the first case, a criterion of image fidelity is proposed in Section 2.4 which gives a numerical measure of the resemblance of image to object in terms of the transmission factors of the optical system. In the second case, assessment is based on the information content of the image in Shannon's sense. This depends not only on the transmission factors of the system but also on the statistical properties of the presumed object set and of the unpredictable fluctuations which necessarily disturb observation; the analysis is carried through in Section 3. In Section 4 the assessment of optical images is discussed in terms of these two criteria.

In this paper we present some new ideas on pattern recognition of bubble chamber photographs. We have found global transformations that reduce circular tracks to a point in a two-dimensional angle-curvature space. The performance of this tracking method on a sample of bubble chamber events is presented and planned improvements are discussed.

Impulse noise removal is a very important preprocessing operation in many computer vision applications. Usually it is accomplished by median filter with excessive sorting and therefore large power. This paper presents a new design of 2D median filter that utilizes a simple conditional filtering technique, executes fewer computations than related designs while achieving superior image quality. Experimental FPGA implementation of the proposed filtering scheme is compact, fast and low-power consuming.

Hough has proposed an interesting and computationally efficient procedure for detecting lines in pictures. This paper points out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further. It also shows how the method can be used for more general curve fitting, and gives alternative interpretations that explain the source of its efficiency.

Walsh functions have become quite useful in the applications of image processing and feature selection. Due to their inherent efficiency of implementation, (they are a subset of the Reed Muller Codes and Hadamard matrices), they have become popular for coding, enhancement and other signal processing tasks. This paper will briefly describe applications in some of these areas with emphasis on a correlation analysis for justification purposes.

In this paper we present a machine vision system for the automatic inspection of defects in textured surfaces found in industry. The defects to be inspected are those that appear as local anomalies embedded in a homogeneous texture. The proposed method is based on a Gabor filtering scheme that computes the output response of energy from the convolution of a textured image with a specific Gabor filter. The best parameters of a Gabor filter are selected so that the energy of the homogeneous texture is zero, and any unpredictable defects will generate significantly large energy values. A simple thresholding scheme then follows to discriminate between homogeneous regions and defective regions in the filtered image. This transforms texture differences into detectable filter output. The experiments on structural textures such as textile fabrics and milled surfaces, and statistical textures such as leather and ,sandpaper have shown the effectiveness of the proposed method.

A data processing system which transforms photographic scans of the moon into rectified lunar pictures has been developed during the LUNAR AIMP satellite program of the National Aeronautics and Space Administration's Goddard Space Flight Center. Three coplanar narrowbeam optical sensors mounted on the spinning satellite provide the photographic input to the system. The satellite's processor determines what lunar image data to transmit, delta-modulating and interleaving these data with necessary navigational parameters. The ground processor reconstitutes the delta-modulated image data into lunar pictures, arranged so as to give the appearance of being the projection of the lunar surface onto one of 24 projection planes. This conversion is performed by first locating each lunar element corresponding to an item of image data. Next the projection plane is selected, either as input or by the program. The lunar elements are then mathematically projected onto the plane. This projection is formatted onto magnetic tape, from which the output picture is generated. In the paper, particular attention is paid to the information flow in the overall spacecraft/ ground-processor system. Some reisults of simulations of portions of the systems by personnel of NASA, Goddard Space Flight Center, and the Image Processing Department of the Federal Systems Division of International Business Machines Corporation (IBM), and of the processing of moon surface imagery on IBM's Electro-Optical Simulation Facility (EOSF) are provided.

This paper presents an automated scoring system for the twist skill in Horizontal bar based on motion image analysis. In this system, training scenes of Horizontal bar are taken by a high-speed video camera, and then a gymnast’s region is extracted from a video image frame by frame based on a background subtraction method. Next, the body axis of the gymnast in the moment when a twist skill completed is estimated from the gymnast’s region. Finally, the deduction point for the twist skill is automatically decided according to the rules described in the Code of Points. In experiments using video images for 26 practices, it was shown that about 80.8% of the correspondence rate between estimated deduction scores and true ones calculated by the correct ‘SCF’ and ‘Body axis’ was obtained. This can be promising as a result at the preliminary stage of this research.

The automatic determination of local similarity between two structured data sets is fundamental to the disciplines of pattern recognition and image processing. A class of algorithms, which may be used to determine similarity in a far more efficient manner than methods currently in use, is introduced in this paper. There may be a saving of computation time of two orders of magnitude or more by adopting this new approach. The problem of translational image registration, used for an example throughout, is discussed and the problems with the most widely used method-correlation explained. Simple implementations of the new algorithms are introduced to motivate the basic idea of their structure. Real data from ITOS-1 satellites are presented to give meaningful empirical justification for theoretical predictions.

In the past, spatial filtering in coherent optical systems has been limited by the inability to realize practically a general complex filter. This paper describes a technique for realizing such a filter, and gives an application of spatial filtering to the problem of detecting isolated signals in a variety of noise backgrounds. The experimental results obtained to date indicate that this technique provides an excellent two-dimensional filtering capability that will play a key role in such problems as shape recognition and signal detection.

In this paper, we propose systems which can render free viewpoint images by using depth image based rendering for live video communications. Experimental results show that an image and depth transmission system is more suitable than an all multi view transmission and an only free viewpoint image transmission system. Especially in the image and depth transmission system, transmitting two images and one depth map, and then predicting the opposite depth map is the best for live communication.

Published papers and reports dealing with data compression, picture properties and models, picture coding and transmission, image enhancement, and human visual information processing are listed.

This bibliography lists published papers that specifically relate to the compression or quality of digitized images of graphics data. By graphics data we mean printed matter, handwriting, line drawings, or any image data that is basically two-level: information on background. The data compression covered here assumes information reduction to images with two levels of signal amplitude followed by redundancy reduction of these binary (i.e., black/white) images. Quality measurements covered are confined to the two-level data resulting from the previous information reduction step for graphics data.

In this paper we describe a new method for creating three-dimensional images using pairs of synthetic aperture radar (SAR) images obtained from a unique collection geometry. This collection mode involves synthetic apertures that have a common center. In this sense the illumination directions for the two SAR images are the same, while the slant planes are at different spatial orientations. The slant plane orientations give rise to cross-range layover (fore-shortening) components in the two images that are of equal magnitude but opposite directions. This differential cross-range layover is therefore proportional to the elevation of a given target, which is completely analogous to the situation in stereo optical imaging, wherein two film planes (corresponding to the two slant planes) result in elevation-dependent parallax. Because the two SAR collections are coherent in this particular collection mode, the images have the same speckle patterns throughout. As a result, the images may be placed into stereo correspondence via calculation of correlations between micro-patches of the complex image data. The resulting computed digital stereo elevation map can be quite accurate. Alternatively, an analog anaglyph can be displayed for 3-D viewing, avoiding the necessity of the stereo correspondence calculation.

In an electro-optical or IR tracking system, a correlation algorithm offers a robust tracking technique in a time-varying scenario. Described in this paper is an automatic target recognition (ATR) algorithm that employs an operator in the loop as an embedded tracking system. The described system combines morphological algorithms with an efficient integer-based correlation tracking algorithm. This algorithm is explored in a time-varying searching and tracking scenario using morphological matched filtering to automatically detect and select objects, with a handover to a correlation tracker. The development of this algorithm using real and synthetic imagery is reviewed, as well as some preliminary results.

Automatic Pattern Recognition and graphical data processing have recently received considerable attention. In addition to analysis and processing of pictorial information, there is a need for interactive display systems to present both intermediate and final processed data. The subject of graphic display terminals has been extensively discussed in the literature. Scan-display systems oriented towards image processing, however, with particular attention to bypassing the central processing unit for as many tasks as possible have not had comparable development. This paper is focused on this latter area.

Using image processing methods and Fourier synthesis techniques similar to those mentioned by Nathan (1970), it has been possible to enhance weak periodic information contained in electron micrographs obtained from what might be characterized as less than ideal thin films. This paper describes the results of such an experiment and illustrates the potential afforded by these computer techniques in an ultrastructural analysis of similar type objects.

This paper presents a summary of a project assessing the utility of hyperspectral imagery to determine cross-country trafficability in support of military operations. Hyperspectral imagery offers new capabilities to assess cross-country trafficability remotely. Development of recommended methodologies and procedures is the major thrust of this research. The use of spectral signature libraries is planned to help define areas to be avoided, such as areas with significant clay content. Likewise, other more compactable soils such as sandy loam can be located and used as preferred routes. This study develops methodologies and provides demonstrations of how hyperspectral imagery can be applied.