Showing papers in "Journal of Electronic Imaging in 1996"

Comparison of video shot boundary detection techniques

Abstract: Many algorithms have been proposed for detecting video shot boundaries and classifying shot and shot transition types. Few published studies compare available algorithms, and those that do have looked at limited range of test material. This paper presents a comparison of several shot boundary detection and classification techniques and their variations including histograms, discrete cosine transform, motion vector, and block matching methods. The perfor- mance and ease of selecting good thresholds for these algorithms are evaluated based on a wide variety of video sequences with a good mix of transition types. Threshold selection requires a trade-off between recall and precision that must be guided by the target application. © 1996 SPIE and IS&T.

Nonlinear unsharp masking methods for image contrast enhancement

Abstract: In the unsharp masking approach for image enhancement, a fraction of the highpass filtered version of the image is added to the original image to form the enhanced version The method is simple, but it suffers from two serious drawbacks First, it enhances the contrast in the darker areas perceptually much more strongly than that in the lighter areas Second, it enhances the noise and/or digitization effects, particularly in the darker regions, resulting in visually less pleasing enhanced images In general, noise can be suppressed with lowpass filters, which are associated with the blurring of the edges On the other hand, contrast can be enhanced with highpass filters, which are associated with noise amplification A reasonable solution, therefore, is to use suitable nonlinear filters which combine the features of both highpass and lowpass filters This paper outlines several new methods of unsharp masking based on the use of such nonlinear filters Computer simulations have verified the superior results obtained using these filters In addition, a new measure of contrast enhancement is introduced which quantitatively supports the improvement obtained using the proposed methods

Morphological scale-space preserving transforms in many dimensions

Abstract: The theory of an image decomposition that we refer to as a sieve is developed for images defined in any finite number of dimensions. The decomposition has many desirable properties in- cluding the preservation of scale-space causality and the localiza- tion of sharp-edged objects in the transformation domain. The de- composition has the additional properties of manipulability, which means that it is easy to construct pattern recognition systems, and scale-calibration, which means that it may be used for accurate measurement. © 1996 SPIE and IS&T.

Set theoretic estimation in color scanner characterization

Abstract: A set theoretic approach for the spectral characterization of a color scanner is described These devices usually employ three channels to obtain a device dependent RGB (red, green, blue) im- age To display/print an image, the device dependent RGB values must be correctly transformed to the color space of the target de- vice To determine accurate and efficient transformations for a num- ber of devices, knowledge of the spectral sensitivity of the scanner is essential Direct measurement of the sensitivity requires a set of expensive narrow band reflectances and is often infeasible Meth- ods that estimate the spectral sensitivity based on measurements with typical reflectance samples are therefore of interest Due to the low dimensionality of the space of object reflectance spectra, this is a highly ill-conditioned problem As a result, conventional estimation techniques that fail to take a priori knowledge into account perform rather poorly on this problem A set theoretic approach that incorpo- rates available a priori knowledge into the estimation framework yields better results Results are presented for a simulated scanner characterization problem and for an actual characterization to dem- onstrate the increased accuracy compared with conventional methods © 1996 SPIE and IS&T

Morphological partitioning of multispectral images

Abstract: The partitioning of an image may be defined as the division of its image plane into image objects. This paper presents a new methodology for partitioning multispectral images. It combines the analysis of the spectral properties of the pixels with the analysis of their spatial properties. Spectral properties are studied in the multivariate histogram of the image, while spatial properties are analyzed in the multispectral gradient of the image. The histogram of the image is first segmented by a nonparametric algorithm. The segmented histogram allows the classification of all image pixels. Each resulting class is then separately filtered in order to remove all classified pixels having a high probability of being misclassified when considering spatial criteria. The filtered classes are used as seeds for boundary detection on the gradient of the original image. The class of the resulting regions is given by the class of the seeds that created those regions.

Color digital halftoning taking colorimetric color reproduction into account

Abstract: Taking colorimetric color reproduction into account, the conventional error diffusion method is modified for color digital half-toning. Assuming that the input to a bilevel color printer is given in CIE-XYZ tristimulus values or CIE-LAB values instead of the more conventional RGB or YMC values, two modified versions based on vector operation in (1) the XYZ color space and (2) the LAB color space were tested. Experimental results show that the modified methods, especially the method using the LAB color space, resulted in better color reproduction performance than the conventional methods. Spatial artifacts that appear in the modified methods are presented and analyzed. It is also shown that the modified method (2) with a thresholding technique achieves a good spatial image quality.

Dynamic-programming-based handwritten word recognition using the Choquet fuzzy integral as the match function

Abstract: The Choquet fuzzy integral is applied to handwritten word recognition. A handwritten word recognition system is described. The word recognition system assigns a recognition confidence value to each string in a lexicon of candidate strings. The system uses a lexicon-driven approach that integrates segmentation and recognition via dynamic programming matching. The dynamic programming matcher finds a segmentation of the word image for each string in the lexicon. The traditional match score between a segmentation and a string is an average. In this paper, fuzzy integrals are used instead of an average. Experimental results demonstrate the utility of this approach. A surprising result is obtained that indicates a simple choice of fuzzy integral works better than a more complex choice.

Classification and overview of research in real-time imaging

Abstract: Real-time imaging has application in areas such as multimedia, virtual reality, medical imaging, and remote sensing and control. Recently, the imaging community has witnessed a tremendous growth in research and new ideas in these areas. To lend structure to this growth, we outline a classification scheme and provide an overview of current research in real-time imaging. For convenience, we have categorized references by research area and application.

Theory of Three Dimensional Computer Graphics

Abstract: Edited by L. Szirmay-Kalos, 421 pages, ISBN 963-05-6911-6, Akademiai Kiado, Budapest, Hungary. Reviewed by Lawrence A. Ray Eastman Kodak Company Transaction Imaging Rochester, New York 14650-0312

Digital adaptive robust algorithms for radar image filtering

Abstract: Novel adaptive robust filtering algorithms applicable to radar image processing are proposed. They take into consideration the peculiarities of radar images and possess a good combination of properties: effective speckle suppression, impulsive noise removal, edge and detail preservation and low computational complexity. The advantages of these digital algorithms are demonstrated by simulated data and images obtained by airborne side-look non SAR radar.

Set operations on closed intervals and their applications to the automatic programming of morphological machines

Abstract: Mathematical morphology on sets can be understood as a formal language, whose vocabulary comprises erosions, dilations, complementation, intersection and union. This language is com- plete, that is, it is enough to perform any set operation. Since the sixties special machines, called morphological machines (MMachs), have been built to implement this language. In the literature, we find hundreds of MMach programs that are used to solve image analysis problems. However, the design of these programs is not an elemen- tary task. Thus, recently much research effort has been addressed to automating the programming of MMachs. A very promising ap- proach to this problem is the description of the target operator by input-output pairs of images and the translation of these data into efficient MMach programs. This approach can be decomposed into two equally important steps: (1) learning of the target operator from pairs of images; (2) search for economical representations for the operators learned. The theory presented in this paper is useful in the second step of this procedure. We present some set operations on collections of closed intervals and give efficient algorithms to per- form them. These operations are used to parallelize MMach pro- grams and to prove the equivalence between distinct MMach pro- grams. © 1996 SPIE and IS&T.

Optimal binary differencing filters: design, logic complexity, precision analysis, and application to digital document processing

Abstract: For given binary image and degradation processes, an optimal mean-absolute-error translation-invariant filter can be designed via the representation of such filters as a union of morphological hit-or-miss transforms. The present paper investigates a different optimization methodology by representing translationinvariant filters as differencing filters. Rather than employing structuring templates to build the entire output image, as is done with direct hit-or-miss representation, differencing filters only employ templates that locate value flips (black-to-white or white-to-black). Differencing filters play a central role in several digital document processing tasks and the paper considers their optimal design. The paper compares the logic designs of differencing and direct hit-ormiss representations, the combinational logic costs of the two representations, and the estimation precision of optimization approaches based on each. Both combinational logic cost and precision are relative to image models. It is also shown how differencing filters are statistically designed and applied in the digital document setting for image restoration and resolution conversion.

Detection of courtesy amount block on bank checks

Abstract: A multi-staged technique for locating the courtesy amount block on bank checks is presented. In the case of a check processing system, many of the proposed methods are not acceptable, due to the the presence of many fonts and text sizes, as well as the short length of many text strings. Particular methods chosen to implement a courtesy amount block locator (CABL) are described. First, the connected components in the image are identified. Next, strings are constructed on the basis of proximity and horizontal alignment of characters. Finally, a set of rules and heuristics are applied to these strings to choose the correct one. The chosen string is only reported if it passes a verification test, which includes an attempt to recognize the currency sign.

Perceived noise versus display noise in temporally filtered image sequences

Abstract: Temporal noise-reduction filtering of image sequences is commonly applied in medical imaging and other applications, and a common assessment technique is to measure the reduction in display noise variance. Theoretically and experimentally, we demonstrate that this is inadequate because it does not account for the interaction with the human observer. Using a new forced-choice method, we compare detectability of low-contrast objects and find a noise level for an unfiltered sequence that gives the same detectability as the filtered sequence. We report the equivalent detectability noise variance ratio, or EDVR. For a digital low-pass filter that reduces the bandwidth by 1/2, display noise reduction predicts an EDVR of 0.5. The measured value averaged over three subjects, 0.93±0.19, compares favorably with the 0.85 predicted from a theoretical human observer model, and both are very close to the value of 1.0 expected for no filtering. Hence, the effective, perceived noise is relatively unchanged by temporal low-pass filtering. The computational observer model successfully evaluates a simple low-pass temporal filter, and we anticipate that it can be used to predict the observer response to other image enhancement filters.

Markov source model for printed music decoding

Abstract: A Markov source model is described for a simple subset of printed music notation that was developed as an extended example of the document image decoding (DID) approach to document image analysis. The model is based on the Adobe Sonata music symbol set and a finite-state language of textual music messages. The music message language is defined and several important aspects of message imaging are discussed. Aspects of music notation that appear problematic for a finite-state representation are identified. Finally, an example of music image decoding and resynthesis using the model is presented. Development of the model was greatly facilitated by the duality between image synthesis and image decoding that is fundamental to the DID paradigm. © 1996 SPIE and IS&T.

Comparative study of skew detection algorithms

Abstract: Document image processing has become an increasingly important technology in the automation of office documentation tasks. Automatic document scanners such as text readers and optical character recognition (OCR) systems are an essential component of systems capable of those tasks. One of the problems in this field is that the document to be read is not always placed correctly on a flat-bed scanner. This means that the document may be skewed on the scanner bed, resulting in a skewed image. This skew has a detrimental effect on document analysis, document understanding, and character segmentation and recognition. Consequently, detecting the skew of a document image and correcting it are important issues in realizing a practical document reader. We describe a new algorithm for skew detection. We then compare the performance and results of this skew detection algorithm to other published methods from O'Gorman, Hinds, Le, Baird, Postl, and Akiyama. Finally, we discuss the theory of skew detection and the different approaches taken to solve the problem of skew in documents. The skew correction algorithm we propose has been shown to be extremely fast, with run times averaging under 0.25 CPU seconds to calculate the angle on a DEC 5000/20 workstation.

Adaptive reconstructive tau-openings: convergence and the steady-state distribution

Abstract: A parameterized t-opening is a filter defined as a union of openings by a collection of compact, convex structuring elements, each scalar multiplied by the parameter. For a reconstructive t-opening, the filter is modified by fully passing any connected com- ponent not completely eliminated. Applied to the signal-union-noise model, in which the reconstructive filter is designed to sieve out clutter while passing the signal, the optimization problem is to find a parameter value that minimizes the MAE between the filtered and ideal image processes. The present study introduces an adaptation procedure for the design of reconstructive t-openings. The adaptive filter fits into the framework of Markov processes, the adaptive pa- rameter being the state of the process. There exists a stationary distribution governing the parameter in the steady state and conver- gence is characterized via the steady-state distribution. Key filter properties such as parameter mean, parameter variance, and ex- pected error in the steady state are characterized via the stationary distribution. The Chapman-Kolmogorov equations are developed for various scanning modes and transient behavior is examined. © 1996 SPIE and IS&T.

Accurate color reproduction of CRT-displayed images as projected 35-mm slides

Abstract: Accurate color reproduction of images presented on a computer-controlled CRT display as projected 35-mm transparencies is a complicated procedure requiring the characterization and control of several imaging processes and the application of appropriate color appearance modeling to account for the changes in viewing conditions. We review a process for image recorder characterization, projection system characterization, and testing of color appearance models for this application. Accurate image recorder characterization was achieved through a combination of empirical modeling of the exposure and processing system and of a physical model of photographic film. The projection system characterization included specification of the spectral properties of the light source, reflectance properties of the viewing screen, and the effects of light exposure and temperature on the photographic transparencies. Color appearance models were used to predict the changes in image color appearance due to changes in media, white point, luminance, and surround. The RLAB model proved to work best in this application.

Real-time inspection by submarine images

Abstract: A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV). Implementation of such procedures gives rise to a human- machine system for underwater pipeline inspection that can auto- matically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video-recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow. © 1996 SPIE and IS&T.

Image scalability using wavelet vector quantization

Abstract: Spatial scalability is a feature referring to image representation in different sizes and is particularly useful in image browsing, as well as in progressive image transmission applications. We propose a new technique for scaling images based on combined wavelet transform and vector quantization (VQ). The proposed technique exploits the spatial scalability feature of wavelet transform and the efficient compression performance of vector quantization. Although VQ is a powerful technique for low bit rate image compression, the label stream VQ is not scalable. Hence, we first propose a scalable VQ algorithm (SVQ) where a smaller-size, coarse quality image can be obtained by decoding a portion of the label bitstream. This image can be further enhanced in size by progressively decoding the remaining bits of the label bitstream. We note that to ensure partial decodability of VQ labels, a multiresolution codebook structure is required. We then apply the SVQ technique in the wavelet domain (WSVQ) where the input image is wavelet-decomposed into three levels and the resulting coefficients are organized into vectors to exploit the intra- and interband correlations. The interband correlations are exploited by employing a nonlinear interpolative vector quantization. Simulation results confirm the superior subjective performance of the proposed technique at a significant reduced computational complexity.

Training-based optimization of soft morphological filters

Abstract: Soft morphological filters form a large class of nonlinear filters with many desirable properties. However, few design methods exist for these filters. This paper demonstrates how optimization schemes, simulated annealing and genetic algorithms, can be employed in the search for soft morphological filters having optimal performance in a given signal processing task. Furthermore, the properties of the achieved optimal soft morphological filters in different situations are analyzed.

Book Rvw: Image Processing, Analysis and Machine Vision. By Milan Sonka, Vaclav Hlavac, and Roger Boyle

Abstract: The title of this book is broad enough for a series of books. So I began reading this book with the preconception that it would not be sufficiently deep to be of any more value than the other image processing books I already own. I was pleasantly surprised. One measure of a book's value is how often a person reaches for it. I have reached for this book many times and have usually found it a source of useful information or leads to more in-depth sources.

Real-time pedestrian counting by active linear cameras

Abstract: Real-time counting of pedestrians traveling through a transport system are increasingly required for traffic control and management by the companies operating such systems. One of the most widely used systems for counting passengers consists of a mechanical gate equipped with a counter. Such simple systems, however, are not able to count passengers jumping above the gates. Moreover, passengers carrying large luggage or bags may meet some difficulties when going through such gates. The ideal solution is a contact-free counting system that would bring more comfort of use for the passengers. For these reasons, we propose to use a video processing system instead of these mechanical gates. The optical sensors discussed offer several advantages, including well-defined detection areas, fast response time, and reliable counting capability. A new technology is developed and tested, based on linear cameras. For the algorithms, thanks to the principle of our system, no assumption is made about the scene being analyzed and the nature of pedestrian movements to enable the system to run in real time. We also consider the problems presented by crowded scenes, when a high incidence of pedestrians occlusions occurs. Preliminary results have shown that this system is very efficient when the passengers crossing the optical gate are well separated. In other cases, such as in compact crowd conditions, good accuracy in terms of counting in real time is demonstrated. These results are illustrated by means of a number of sequences shot in field conditions.

Detection and location of multicharacter sequences in lines of imaged text

Abstract: A system for detecting and locating user-specified search strings, or phrases, in lines of imaged text is described. The phrases may be single words or multiple words, and may contain a partially specified word. The imaged text can be composed of a number of different fonts and graphics. Textlines in a deskewed image are hypothesized using multiresolution morphology. For each textline, the baseline, topline and x-height are identified by simple statistical methods and then used to normalize each textline bounding box. Columns of pixels in the resulting bounding box serve as feature vectors. One hidden Markov model is created for each user-specified phrase and another represents all text and graphics other than the user-specified phrases. Phrases are identified using Viterbi decoding on a spotting network created from the models. The operating point of the system can be varied to trade off the percentage of words correctly spotted and the percentage of false alarms. Results are given using a subset of the UW English Document Image Database I.

Morphological pseudo bandpass image decompositions

Abstract: A morphological bandpass filter would, ideally, strictly limit the sizes of all features in an image to lie between the sizes of two similarly shaped but differently scaled structuring elements. A morphological bandpass decomposition of an image would be a disjoint set of morphological bandpass images with features of increasing size such that the set sums to the original image. Such strict bandpass limitations in size are not possible in general for arbitrary structuring element families. Hence, a true bandpass decomposition is not generally possible. Pseudo bandpass decompositions, in which intraband size limitations are relaxed, are possible and can be useful image analysis tools. Four pseudo bandpass image decompositions are described, one of which, the opening spectrum, is relatively well known and three of which are new. They are a decomposition derived from iteration of the top-hat transform, a morphological reconstruction of a Euclidean (quasi) granulometry, and a reconstruction of the opening spectrum. Properties of the opening spectrum and the top-hat transform are reviewed. The tophat spectrum is defined, some of its properties are deduced, and it is compared to the opening spectrum. The reconstruction-based decompositions are defined and compared to the others. Comparative examples are given and a practical use described.

Pyramidal approach to license plate segmentation

Abstract: Car identification is a goal in traffic control, transport planning, travel time measurement, managing parking lot traffic and so on. Most car identification algorithms contain a standalone plate segmentation process followed by a plate contents reading. A pyramidal algorithm for license plate segmentation, looking for textured regions, has been developed on a PC based system running Unix. It can be used directly in applications not requiring real time. When input images are relatively small, real-time performance is in fact accomplished by the algorithm. When using large images, porting the algorithm to special digital signal processors can easily lead to preserving real-time performance. Experimental results, for stationary and moving cars in outdoor scenes, showed high accuracy and high scores in detecting the plate. The algorithm also deals with cases where many character strings are present in the image, and not only the one corresponding to the plate. This is done by the means of a constrained texture regions classification.

Motion-compensated visual pattern image sequence coding for full-motion multisession videoconferencing on multimedia workstations

Abstract: Motion-compensated visual pattern image sequence coding (MCVPISC) is an improved motion-compensated version of the visual pattern image sequence coding (VPISC) encoder. It is a high-performance video codec that is easily implemented in soft- ware. The MCVPISC codec is intended for real-time desktop com- puter applications such as multimedia delivery and local area net- work and point-to-point (modem) video conferencing. We describe a version of MCVPISC that has achieved bit rates of 0.15 bits/pixel or better for MPEG-2 test sequences (source encoding reduces this bit rate by about half). The computational complexity of the mono- chrome and color versions of the encoder is less than three integer operations per pixel. The decoder is bounded between 0.016 and 0.125 logical and integer operations per pixel. A prototype video conferencing system based on the MCVPISC codec has been implemented. The system hardware is comprised of two multimedia personal computers, two camcorders, two frame grabbers, and an ethernet connection. The prototype system software has a simple structure and runs under DOS and Windows™ 3.1. It includes a user interface, a video I/O interface, an event driven network inter- face, and a free running or frame synchronous video codec that also acts as the controller for the video and network interfaces. We have demonstrated that this prototype can support up to five full duplex full-motion video conferencing sessions. Future work will concen- trate on expanding the prototype to support synchronous audio, multiple hardware and software platforms, and network protocols. © 1996 SPIE and IS&T.

Scanline algorithms in the JPEG discrete cosine transform compressed domain

Abstract: Scanline algorithms are popular in computer graphics for complex geometric manipulations. The main characteristic of scanline algorithms is that a geometric transformation is decomposed into multipass transforms with each pass operating only along row or column scanlines. This leads to conversion of 2-D image manipulation problems to straightforward 1-D problems resulting in simple and systematic methods. The goal of this work is to examine the scanline approach for manipulation of transform-compressed images without decompressing them. We show how the scanline algorithms for rotation and projective mapping can be developed for JPEG/DCT images. The performance of the proposed scanline algorithms is evaluated with respect to quality, speed, and control and memory overhead.

Restoration of images scanned in the presence of vibrations

Abstract: Images scanned in the presence of mechanical vibration are subject to artifacts such as brightness fluctuation and geometric warping. The goal of the present study is to characterize these distortions and develop a restoration algorithm to invert them, hence producing an output digital image consistent with a scanner operating under ideal uniform motion conditions. The image restoration algorithm described in this paper makes use of the instantaneous velocity of the linear sensor array to reconstruct an underlying piecewise constant or piecewise linear model of the image irradiance profile. That reconstructed image is then suitable for resampling under ideal scanning conditions to produce the restored output digital image. We demonstrate the algorithm on simulated scanned imagery with typical operating parameters.