Showing papers in "Journal of Electronic Imaging in 1995"

Performing color space conversions with three-dimensional linear interpolation

Abstract: Three-dimensionalinterpolation is suitable for many kinds of color space transformations. We examine and analyze several linear interpolation schemes-some standard, some known, and one novel. An interpolation algorithm design is divided into three parts: packing (filling the space of the input variable with sample points), extraction (selecting from the constellation of sample points those appropriate to the interpolation of a specific input point), and calculation (using the extracted values and the input point to determine the interpolated approximation to the outputpoint). We focus on regular (periodic) packing schemes. Seven principles govern the design of linear interpolation algorithms: 1) Each sample point should be used as a vertex of as many polyhedra as possible; 2) the polyhedra should completely fill the space; 3) polyhedra that share any part of a face must share the entire face; 4) the polyhedra used should have the fewest vertices possible; 5) polyhedra should be small; 6) in the absence of information about cuivature anisotropy, polyhedra should be close to regular in shape; and 7) polyhedra should be of similar size. A test for interpolation algorithm performance in performing actual color space conversions is described, and results are given for an example color space conversion using several linear interpolation methods. The extractions from cubic, body-centered-cubic, and face-centered-cubic lattices are described and analyzed. The results confirm Kanamori's claims for the accuracy of PRISM interpolation; it comes close to the accuracy of trilinear interpolation with roughly three-quarters the computations. The results show that tetrahedral interpolation, with close to half the computational cost of tnlinear interpolation, is capable of providing better accuracy. Of the tetrahedral interpolation techniques, one diagonal extraction from cubic packing is useful as a general-purpose color space interpolator...

Experimental evaluation of psychophysical distortion metrics for JPEG-encoded images

Abstract: Two experiments for evaluating psychophysical distortion metrics in Joint Photographic Experts Group (JPEG) encoded images are described. The first is a threshold experiment, in which subjects determined the bit rate or level of distortion at which distortion was just noticeable. The second is a suprathreshold experiment in which subjects ranked image blocks according to perceived distortion. The results of these experiments were used to determine the predictive value of a number of computed image distortion metrics. It was found that mean-square-error is not a good predictor of distortion thresholds or suprathreshold perceived distortion. Some simple pointwise measures were in good agreement with psychophysical data; other more computationally intensive metrics involving spatial properties of the human visual system gave mixed results. It was determined that mean intensity, which is not accounted for in the JPEG algorithm, plays a significant role in perceived distortion.

Colorimetric characterization of a desktop drum scanner using a spectral model

Abstract: A desktop drum scanner was colorimetrically characterized to an average CIELAB error of less than unity for Kodak Ektachrome transparencies and Ektacolor paper, and Fuji Photo Film Fujichrome transparencies and Fujicolor paper Independent verification on spectrally similar materials yielded an average ΔE* ab error of less than 21 The image formation of each medium was first modeled using either Beer-Bouguer or Kubelka-Munk theories and eigenvector analysis Scanner digital values were then empirically related to dye concentrations using polynomial step-wise multiple-linear regression These empirical matrices were required because the scanner's system spectral responsivities had excessively wide bandwidths From these estimated dye concentrations, either a spectral transmittance or spectral reflectance factor was calculated from an a priori spectral analysis of each medium The spectral estimates can be used to calculate tristimulus values for any illuminant and obsetver of interest The methods used in this research are based on historical methods commonly used in photographic science

Image encryption method using a class of fractals

Abstract: We present a cryptographic scheme for encrypting 2-D gray scale images by using a large family of fractals. This scheme is based on a transposition of the image elements implemented by a generator of 2-D hierarchical scanning patterns producing a large subset of the (n2)! possible orders defined on a 2-0 image of n x n elements. Each pattern defines a distinct order of pixels and can be described by an expression, which is considered as the key of the transposition. This transposition cipher can easily be combined with various substitution ciphers, producing efficient product ciphers operating on pictorial data. Two such ciphers are constructed and their effects on real gray value images are shown. Encryption and decryption algorithms are derived from a parailel algorithm implementing the creation of the family of scanning patterns.

Optimized universal color palette design for error diffusion

Abstract: Currently, many low-cost computers can only simultaneously display a palette of 256 colors. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L *a *b , but also accounts for the lowpass characteristic of human contrast sensitivity.

Design and realization of optimal color filters for multi-illuminant color correction

Abstract: A method of selecting optimal color filters to perform accurate multi-illuminant color correction is reviewed. The transmittances for a set of filters obtained by the method were provided to a color filter manufacturer. The manufacturer used a dichroic filter modeling program to produce transmittances that satisfied the physical constraints of the manufacturing process and approximated the optimal filter transmittances. The ideal and manufacturable filters are compared through computer simulation and their accuracy assessed during the CIE Δ E L*a*b measure. The results show that the unconventional shapes of the optimal filters can be weil approximated by actual filters with slight degradation in performance.

Viewing model for virtual environment displays

Abstract: We present a viewing model that is appropriate for several types of displays used in virtual environment systems, including head-mounted displays and head-tracked stationary displays. The model accounts for arbitrary size, placement, and orientation of the display images, and thus is suitable for various display designs. We provide algorithms for calculating stereoscopic viewing and projection matrices. The tracking algorithm models the position and orientation of the tracker's emitter and the displacement between the sensor and the user's eyes. The algorithms are presented as parameterized homogeneous transforms. We also discuss features that can be used to avoid accommodation/convergence conflicts. The advantages of this viewing model and algorithm are the elimination of possible vertical parallax, an undistorted perception of depth, and reduction of eye fatigue due to excessive parallax. All of these factors contribute to improved comfort and utility for the operator.

Comparative performance evaluation of various fringe thinning algorithms in photomechanics

Abstract: In recent years several algorithms have been reported for automating fringe data collection in photomechanics using the technique of digital image processing (DIP). Recent advances in phase shifting interferometry have offered some hope for full automation of static problems. However, for real-time dynamic studies conventional recording of fringes is a must. Fringe thinning is a very crucial step in extracting data for further processing. The various DIP algorithms for fringe thinning are surveyed and an attempt is made to explain better the mechanism of fringe skeleton extraction by various algorithms. The algorithm of Ramesh and Pramod is improved to extract fringe skeletons from saddle points in the fringe field. A cornparative performance evaluation of these algorithms is discussed with respect to the quality and accuracy of fringe skeleton extracted and the processing time. Performance evaluation is done on a few computer-generated. test images and also on images recorded by the technique of photoelasticity. The improved version of the algorithm of Ramesh and Pramod is found to give better fringe skeletons; it is also the fastest and the processing time is an order of magnitude less than the other algorithms. It is proposed that these computergenerated test images could be used as standard test images for checking the performance of any new fringe thinning algorithm.

Color space selection for JPEG image compression

Abstract: The Joint Photographic Experts Group's image compression algorithm has been shown to provide a very efficient and powerful method of compressing images. However, there is little substantive information about which color space should be utilized when implementing the JPEG algorithm. Currently, the JPEG algorithm is set up for use with any three-component color space. The objective of this research is to determine whether or not the color space selected will significantly improve the image compression. The RGB, XYZ, YIQ, CIELAB, CIELUV, and CIELAB LCh color spaces were examined and compared. Both numerical measures and psycho-physical techniques were used to assess the results. The final resuLts indicate that the device space, RGB, is the worst color space to compress images. In comparison, the nonlinear transforms of the device space, CIELAB and CIELUV, are the best color spaces to compress images. The XYZ, YIQ, and CIELAB LCh color spaces resulted in intermediate levels of compression.

Modeling vibration-induced halftone banding in a xerographic laser printer

Abstract: In a raster scanning printer, a laser beam is scanned across a photoreceptor in a direction perpendicular to the photoreceptor motion. When there is vibratory motion of the photoreceptor or wobble in the polygon mirror, the raster lines on the photoreceptor will not be evenly spaced. We analyze the positioning error and show that fractional raster spacing error is equal to photoreceptor fractional velocity error. These raster position errors can result in various print defects, of which halftone banding is the dominant defect. The dependences of halftone banding are examined using a first-order geometry-based printing model, an exposure model, and a more sophisticated laser imaging model coupled with a xerography model. The system model is used to calculate print reflectance modulation due to vibrations in both charged-area and discharged-area development modes using insulative or conductive development. System parameters examined are halftone frequency, raster frequency, average reflectance, vibration frequency, and multiple-beam interlace spacing.

Design of image-adaptive quantization tables for JPEG

Abstract: The rate-distortion trade-off in the discrete cosine transform- based coding scheme in ISO/JPEG is determined by the quantization table. To permit a different quality to be selected by a user, a common practice is to scale the standard quantization tables that have been empirically determined from psychovisual experiments. In this paper, an algorithm is presented to generate a quantization table that is optimized for a given image and for a given distortion. The computationalcomplexity of this algorithm is reduced compared to other techniques. The optimized, image-adaptive quantization table typically yields an improvement of 15% to 20% in bit rate compared to the use of standard, scaled quantization tables. Once an optimized quantization table has been generated for a specific image, it can also be applied to other images with similar content with a small sacrifice in bit rate.

Cathode-ray-tube to reflection-print matching under mixed chromatic adaptation using RLAB

Abstract: Color-appearance models are used to relate chromatic stimuli viewed under one set of viewing and illuminating conditions to a differing set such that when each stimulus is viewed in its respective conditions, the stimuli match in color appearance. These models assume the observer has a steady-state adaptation to each condition. In practice, observers often view stimuli under mixed adaptation; this could occur when viewing CRT and reflection-print stimuli simultaneously. A visual experiment was performed to determine whether the RLAB color-appearance model could be used successfully to generate reflection prints that match the appearance of the CRT when viewed under mixed states of adaptation and in turn as stand-alone images viewed under a single state of adaptation. Sixteen observers viewed four pictorial images displayed on a D 65 balanced CRT display in a room lit with cool-white fluorescent luminaries. The RLAB color-appearance model was used to calculate corresponding images where the observer's state of chromatic adaptation was assumed to be one of the following: adaptation to each device condition, a single adaptation at the midpoint of the two device conditions, adaptation to the CRT condition and a print adaptation shifted 25% toward the CRT condition, adaptation to the print condition and a CRT adaptation shifted 25% toward the print condition, and a CRT condition shifted 25% toward the print condition and a print condition shifted 25% toward the CRT condition. Each condition was compared pairwise and Thurstone's law of comparative judgments was used to calculate interval scales of quality. Observers first judged the reflection prints adjacent to the CRT display selecting the image closest in color appearance to the CRT image; they also categorized the closest image as "acceptable, " "marginally acceptable," or "not acceptable." The images were again scaled except the display was turned off; this determined the best standalone color reproduction.

Image segmentation using fuzzy rules derived from K-means clusters

Abstract: Image segmentation is one of the most important steps in computerized systems for analyzing geographic map images. We present a segmentation technique, based on fuzzy rules derived from the K-means clusters, that is aimed at achieving human-like performance. In this technique, the K-means clustering algorithm is first used to obtain mixed-class clusters of training examples, whose centers and variances are then used to determine membership functions. Based on the derived membership functions, fuzzy rules are learned from the K-means cluster centers. In the map image segmentation, we make use of three features, difference intensity, standard deviation, and a measure of the local contrast, to classify each pixel to the foreground, which consists of character and fine patterns, and to the background. A centroid defuzzification algorithm is adopted in the classification step. Experimental results on a database of 22 gray-scale map images show that the technique achieves good and reliable results, and is compared favorably with an adaptive thresholding method. By using K-means clustering, we can build a segmentation system of fewer rules that achieves a segmentation quality similar to that of using the uniformly distributed triangular membership functions with the fuzzy rules learned from all the training examples.

On the application of Gibbs random field in image processing: from segmentation to enhancement

Abstract: The Gibbs random field (GRF) has proved to be a simple and practical way of parameterizing the Markov random field, which has been widely used to model an image or image-related process in many image processing applications. In particular, the GRF can be employed to construct an efficient Bayesian estimation that often yields optimal results. We describe how the GRF can be efficiently incorporated into optimization processes in several representative applications, ranging from image segmentation to image enhancement. One example is the segmentation of computerized tomography (CT) volumetric image sequence in which the GRF has been incorporated into K-means clustering to enforce the neighborhood constraints. Another example is the artifact removal in discrete cosine transform-based low bit rate image compression where GRF has been used to design an enhancement algorithm that reduces the "blocking effect" and the 'Wnging effect" while still preserving the image details. The third example is the integration of GRF in a wavelet-based subband video coding scheme in which the highfrequency subbands are segmented and quantized with spatial constraints specified by a GRF, and the subsequent enhancement of the decompressed images is accomplished by smoothing with another type of GRF. With these diverse examples, we are able to demonstrate that various features of images can all be properly characterized by a GRF. The specific form of the GRF can be selected according to the characteristics of an individual application. We believe that the GRF is a powerful tool to exploit the spatial dependency in various images, and is applicable to many image processing tasks.

Three-dimensional histogram visualization in different color spaces and applications

Abstract: A visualization procedure for the 3-D histogram of color images is presented. The procedure assumes that the histogram is available as a table that associates to a pixel color the number of its appearances in the image. The procedure runs for the RGB, YMC, HSV, HSL, L*a*b*, and L*u*v* color spaces and it is easily extendable to other color spaces if the analytical form of color transformations is available. Each histogram value is represented in the color space as a colored ball, in a position corresponding to the place of the color in the space. A simple drawing procedure is used instead of more complicated 3-D rendering techniques. The 3-D histogram visualization offers a clear and intuitive representation of the color distribution of an image. The procedure is applied to derive a clusterization technique for color classification and visualize its resuIts, to display comparatively the gamut of different color devices, and to detect the misalignment of the Rc3B planes of a color image. Diagrams illustrating the visualization procedure are presented for each application.

Algorithm for the computation of region-based image edge profile acutance

Abstract: We propose an algorithm for the computation of a region-based measure of image edge profile (IEP) acutance based on graylevel variations across the boundary of an object. A procedure to calculate the acutance based on region growing and a root-mean-squared gradient measure across region boundaries has been designed and implemented. After testing the algorithm on various images, it is shown that this measure of acutance can accurately reflect changes in the appearance of objects due to blurring and sharpening operations. Using this technique, it should be possible to quantify the level of enhancement in a digital image by calculating the acutance before and after the enhancement operation. The measure should also be useful in comparing specific features or regions of interest in images produced by different imaging systems.

New edge-enhanced error diffusion algorithm based on the error sum criterion

Abstract: new edge-enhanced error diffusion algorithm, based on Eschbach's algorithm, is proposed. Thick-edged artifacts as well as small edge-enhancement effects for the bright or dark pixel values are observed in the previous algorithm. By analyzing the phenomena, a new improved algorithm is proposed by using the diffused error sum and input pixel value. An input pixel is classified into a normal- or edge-region pixel based on the error sum criterion. A new error calculation is then employed for the edge region pixel, while conventional error calculation is used for the normal-region pixel. The proposed method requires only a few additional calculations and provides edge-enhanced binary output images. The edges are in fluenced less by the brightness offset, and thick-edged artifacts are reduced.

ELPIDA: a general architecture for medical imaging systems supporting telemedicine applications

Abstract: During the next years, profound changes are expected in computer and communication technologies that will offer the medical imaging systems (MIS) industry a challenge to develop advanced telemedicine applications of high performance. Medical industry, vendors, and specialists need to agree on a universal MIS structure that will provide a stack of functions, protocols, and interfaces suitable for coordination and management of high-level image consults, reports, and review activities. Doctors and engineers have worked together to determine the types, targets, and range of such activities within a medical group working domain and to posit their impact on MIS structure. As a result, the fundamental MIS functions have been posed and organized in the form of a general MIS architecture, denoted as ELPIDA. The structure of this architecture was kept as simple as possible to allow its extension to diverse multimode operational schemes handling medical and conversational audiovisual information of different classes. The fundamentals of ELPIDA and pulmonary image diagnostic aspects have been employed for the development of a prototype MIS.

Model-based neural evaluation and iterative gradient optimization in image restoration and statistical filtering

Abstract: An optimal model-based neural evaluation algorithm and an iterative gradient optimization algorithm used in image restoration and statistical filtering are presented. The relationship between the two algorithms is studied. We show that under the symmetric positive-definite condition, a condition easily satisfied in restoration and filtering, intra-pixel sequential processing (IPSP) of model-based neuron evaluation is equivalent to the iterative gradient optimization algorithm. We also show that although both methods provide feasible solutions to fast spatial domain implementation of restoration and filtering techniques, the iterative gradient algorithm is in fact more efficient than the IPSP neuron evaluation method. Visual examples are provided to compare the performance of the two approaches.

Comparison of wavelet scalar quantization and JPEG for fingerprint image compression

Abstract: An overview of the wavelet scalar quantization (WSQ) and Joint Photographic Experts Group (JPEG) image compression algorithms is given. Results of application of both algorithms to a database of 60 fingerprint images are then discussed. Signal-to-noise ratio (SNR) results for WSQ, JPEG with quantization matrix (QM) optimization, and JPEG with standard QM scaling are given at several average bit rates. In all cases, optimized-QM JPEG is equal or superior to WSQ in SNR performance. At 0.48 bit/pixel, which is in the operating range proposed by the Federal Bureau of Investigation (FBI), WSQ and QM-optimized JPEG exhibit nearly identical SNR performance. In addition, neither was subjectively preferred on average by human viewers in a forced-choice image-quality experiment. Although WSQ was chosen by the FBI as the national standard for compression of digital fingerprint images on the basis of image quallty that was ostensibly superior to that of existing internationalstandard JPEG, it appears possible that this superiority was due more to lack of optimization of JPEG parameters than to inherent superiority of the WSQ algorithm. Furthermore, substantial worldwide support for JPEG has developed due to its status as an international standard, and WSQ is significantly slower than JPEG in software implementation. Still, it is possible that WSQ enhanced with an optimal quantizer-design algorithm could outperform JPEG. This is a topic for future research.

Hardware implementation of a motion-compensating format converter

Abstract: The realization of a TV-interlaced (TVI) to HDTV-interlaced (HDI) real-time format converter for studio applications is described. The conversion is performed by motion-compensated 3-D interpolation. The estimation of motion is based on hiera rchical block matching. Reliability checking of motion vectors is applied to achieve high picture quality. Furthermore, various picture classification algorithms are utilized to improve the reliability of motion vectors. This format converter has been developed using specially designed VLSI chips, digital signal processors, and field-programmable gate arrays for the reduction of hardware. The special VLSI chips have been developed using semicustom and fuli-custom design techniques. Besides employment within the format converter they are suitable for various applications in video processing.

Improved Chen-Smith image coder

Abstract: A new transform coder based on the zonal sampling strategy, which outperforms the JPEG baseline coder with comparable computational complexity, is presented. The primary transform used is the 8- × 8-pixel-block discrete cosine transform, although it can be replaced by other transforms, such as the lapped orthogonal transform, without any change in the algorithm. This coder is originally based on the Chen-Smith coder, therefore, we call it an improved Chen-Smith (ICS) coder. However, because many new features were incorporated in this improved version, it largely outperforms its predecessor. Key approaches in the ICS coder, such as a new quantizer design, arithmetic coders, noninteger bit-rate allocation, decimated variance maps, distance-based block classification, and human visual sensitivity weighting, are essential for its high performance. Image compression programs were developed and applied to several test images. The results show that the ICS performs substantially better than the JPEG coder.

Fractal-based method for color image compression

Abstract: A fractal-based method for color image compression is presented. The method transforms the direct color components into three approximate principal components and applies a fractal-based compression method developed for gray-scale images to each new component. The main principal component, which contains a large amount of energy, is coded with high accuracy, while the other two components can be coded at lower accuracy and a very high compression ratio. The principal-component-based method gives an overall higher quality in the reconstructed image at a similar compression rate compared with compression based on other linear transforms of the color space.

Digital halftoning using two-dimensional carriers with a noninteger period

Abstract: Among the various digital haiftoning methods, carrier procedures have the advantage of being fast and requiring few computational resources. However, because they are pixel-oriented a!- gorithms, they offer!ess flexibility than more complex algorithms that involve the information from a neighborhood or the entire image in the quantization of each pixel. By introducing noninteger ratios between the carrier and raster period, the carrier procedure can be adapted to the spectral characteristics of the visual system. The spectral noise distribution can be optimized in this regard for twodimensional, periodic carriers with arbitrary shape.

Analysis of color images of natural scenes

Abstract: A clustering algorithm for analyzing and partitioning the color images of natural scenes is described. The proposed method operates in the 1976 CIE (l*a*b*)uniform color coordinate system. It detects image clusters in some circular-cylindrical decision elements of the color space. This estimates the clusters' color distributions without imposing any constraints on their forms. Surfaces of the decision elements are formed with constant lightness and constant chromaticity loci. Each surface is obtained using only 1-D histogramsof the L*,H,C* cylindrical coordinates of the image data or the extracted feature vector. The Fisher linear discriminant method is then used to project simultaneously the detected color clusters onto a line for 1-0 thresholding. This permits utilization of all the color properties for segmentation, and inherently recognizes their respective cross correlation. In this respect, the proposed algorithm also differs from the multiple histogram-basedthresholding schemes in that it generates more reliable gross segmentation results.

Recognition of a low-resolution document consisting of Korean and English characters

Abstract: We propose an efficient algorithm that recognizes handwritten Korean and English characters in a low-resolution document. For a user-friendly input system for low-resolution documents consisting of two different sets of characters obtained by a facsimile or scanner, we propose a document-recognition algorithm utilizing several effective features (partial projection, the number of cross points, and distance features) and the membership function of the fuzzy set theoty. Via computer simulation with several test documents, we show the effectiveness of the proposed recognition algorithm for both printed and handwritten and Korean and English characters in a low-resolution document.

Normalized cross-correlation: the contrast-dependent problem and its solution

Abstract: Normalized cross-correlation (NCC) measure has often been used for image matching due to its invariance under changes in image bias and gain. We address the problem of using it for pattern matching in practical imaging systems. It presents an empirical relationship between the contrast level in an image and its bestmatched NCC. It further derives and confirms this relationship theoretically. A novel, adaptive method of adjusting the best-matched NCC based on the established relationship is subsequently presented to alleviate the problem of pattern matching in practical imaging systems. Experimental results on real scenes of both low and high contrast images are finally presented to demonstrate the usefulness of the proposed method.

Feature-preserving thinning algorithm for optical character-recognition

Abstract: We propose an improved thinning algorithm. Basically, the algorithm uses a 3×3 window to accommodate an eight-neighbor skeleton in each thinning iteration. This algorithm overcomes many thinning problems, such as Y-shaped distortions, spiky skeletons, and skeleton shortening, and thus preserves precise features of digital character patterns. By using this thinning algorithm, better structural features of a character pattern can be provided to an optical character recognition system, such that accurate recognition results can be achieved.

Quantitative analysis of coronary dynamics by time-dependent ultrasound imaging

Abstract: Intravascular ultrasound imaging is a new technique that displays information on lumen and arterial walls, and is capable of providing real-time monitoring of cross-sectional high-resolution images. This technique has potential application for studying the dynamics of the arterial wall with respect to the presence or absence of pathology and the vascular response to physiological or pharmacological stimuli. Although the extraction of information related to coronary dynamics and wall pathologies is possible by manual procedures, it is very time consuming and influenced by intra- and interobserver errors. We developed an evaluation system for analyzing 3-D spaces defined by digitized cross-sectional ultrasound images of coronaries quantifying the vasomotion in relation to the morphology of the arterial wall. Sequences of echographic images were obtained and recorded as ordered stacks of 2-D frames on a VHS videotape. For each image, an automatic lumen edge segmentation was performed, then 3-0 reconstruction was obtained to evaluate time-dependent lumen and vessel wall changes. These 3-D representations serve to demonstrate dynamic phenomena and to perform quantitative analyses (e.g., area/hemidiameter variations, projections, sections, "carving," etc.).

Prototype model for automatic integrated circuit bonding inspection

Abstract: A simple but comprehensive prototype model developed to automate the inspection of wedge bonds in the IC assembly process is described The defects associated with the bond quality are classified into four categories: size, shape, position, and dimension The bond is inspected sequentially for each categoiy of defects and is rejected without further processing when any defect is detected The procedure adopted in the prototype is as follows A global thresholding technique automatically binarizes the intensity image of the bond Simple features such as the pixel count, minimum enclosing rectangle, centroid, and median are used to verify the specifications related to the size and shape An intelligent scanning technique inspects the position-related specifications in addition to identifying the wire and tall positions of the bond The dimensions of the bond are determined using projection information Most importantly, this model is capable of determining the wire position, which is useful in inspecting wire-related defects Experiments conducted on actual sample ICs have shown a 100% success rate