Roland T. Chin

On image analysis by the methods of moments

Various types of moments have been used to recognize image patterns in a number of applications. A number of moments are evaluated and some fundamental questions are addressed, such as image-representation ability, noise sensitivity, and information redundancy. Moments considered include regular moments, Legendre moments, Zernike moments, pseudo-Zernike moments, rotational moments, and complex moments. Properties of these moments are examined in detail and the interrelationships among them are discussed. Both theoretical and experimental results are presented. >

On the detection of dominant points on digital curves

A parallel algorithm is presented for detecting dominant points on a digital closed curve. The procedure requires no input parameter and remains reliable even when features of multiple sizes are present on the digital curve. The procedure first determines the region of support for each point based on its local properties, then computes measures of relative significance (e.g. curvature) of each point, and finally detects dominant points by a process of nonmaximum suppression. This procedure leads to the observation that the performance of dominant points detection depends not only on the accuracy of the measure of significance, but also on the precise determination of the region of support. This solves the fundamental problem of scale factor selection encountered in various dominant point detection algorithms. The inherent nature of scale-space filtering in the procedure is addressed, and the performance of the procedure is compared to those of several other dominant point detection algorithms, using a number of examples. >

Automated Visual Inspection: A Survey

This paper surveys publications, reports, and articles dealing with automated visual inspection for industry. The references are organized according to their contents: overview and discussions, rationales, components and design considerations, commercially available systems, applications. A number of applications and their inspection methodologies are discussed in detail: the inspection of printed circuit boards, photomasks, integrated circuit chips. Other inspection applications are listed as a bibliography. A list of selectively annotated references in commercially available visual inspection tools is also included.

Digital restoration of multichannel images

The Wiener solution of a multichannel restoration scheme is presented. Using matrix diagonalization and block-Toeplitz to block-circulant approximation, the inversion of the multichannel, linear space-invariant imaging system becomes feasible by utilizing a fast iterative matrix inversion procedure. The restoration uses both the within-channel (spatial) and between-channel (spectral) correlation; hence, the restored result is a better estimate than that produced by independent channel restoration. Simulations are also presented. >

Analysis of thinning algorithms using mathematical morphology

A precise definition of digital skeletons and a mathematical framework for the analysis of a class of thinning algorithms, based on morphological set transformation, are presented. A particular thinning algorithm (algorithm A) is used as an example in the analysis. Precise definitions and analyses associated with the thinning process are presented, including the proof of convergence, the condition for one-pixel-thick skeletons, and the connectedness of skeletons. In addition, a necessary and sufficient condition for the thinning process in general is derived, and an algorithm (algorithm B) based on this condition is developed. Experimental results are used to compare the two thinning algorithms, and issues involving noise immunity and skeletal bias are addressed. >

Least squares restoration of multichannel images

Multichannel restoration using both within- and between-channel deterministic information is considered. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images yield suboptimal results when applied to multichannel images, since between-channel information is not utilized. Multichannel least squares restoration filters are developed using the set theoretic and the constrained optimization approaches. A geometric interpretation of the estimates of both filters is given. Color images (three-channel imagery with red, green, and blue components) are considered. Constraints that capture the within- and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. A spatially adaptive, multichannel least squares filter that utilizes local within- and between-channel image properties is proposed. Experiments using color images are described. >

A one-pass thinning algoruthm and its parallel implementation

Abstract This paper describes a one-pass thinning algorithm that requires only a single cycle of parallel operations per iteration. The major difference between this algorithm and the usual multiple-pass 3 × 3 operators is that it uses two restoring templates (a 1 × 4 and a 4 × 1 operator) to deal with the breakage and disappearance of horizontal and vertical two pixel wide limbs. Connectedness of skeletons has been verified and limitations of the algorithm have been discussed. Results of a comparative study are also presented. In addition, a realization of the thinning algorithm is suggested with processing speed limited only to the propagation delays of logic gates.

One-pass parallel thinning: analysis, properties, and quantitative evaluation

A one-pass parallel thinning algorithm based on a number of criteria, including connectivity, unit-width convergence, medial axis approximation, noise immunity, and efficiency, is proposed. A pipeline processing model is assumed for the development. Precise analysis of the thinning process is presented to show its properties, and proofs of skeletal connectivity and convergence are provided. The proposed algorithm is further extended to the derived-grid to attain an isotropic medial axis representation. A set of measures based on the desired properties of thinning is used for quantitative evaluation of various algorithms. Image reconstruction from connected skeletons is also discussed. Evaluation shows that the procedures compare favorably to others. >

Automated visual inspection: 1981 to 1987

Abstract This bibliography lists journal publications, conference papers, research technical reports, and articles from trade journals on automated visual inspection for industry which were published during the years from 1981 to 1987. More than 600 references are included. References are organized into 13 categories according to subject matter. The categories are (1) books, (2) conferences and workshops, (3) general discussions and surveys, (4) inspection of printed circuit patterns, (5) inspection of solder joints, (6) inspection of microcircuit photomasks, (7) inspection of integrated circuits and hybrids, (8) inspection of other electrical and electronics components, (9) surface inspection, (10) X-ray inspection, (11) other inspection applications, (12) system components, and (13) inspection algorithms. References listed in each category are arranged in chronological order. The purpose is primarily to provide a complete bibliography for those interested in automated visual inspection. Some general observations have been made for the above areas of activity summarizing the advances that have taken place and the problems that remain to be solved.

Quantitative evaluation of some edge-preserving noise-smoothing techniques

Abstract A quantitative evaluation of several edge-preserving noise-smoothing techniques is presented. All of the techniques evaluated are devised to preserve edge sharpness while achieving some degree of noise cleaning. They are based on local operations on neighboring points and all of them can be iterated. They are unweighted neighbor averaging (AVE), K-nearest neighbor averaging (KAVE), the edge and line weights method (EDLN), gradient inverse weighted smoothing (GRADIN), maximum homogeneity smoothing (MAXH), slope facet model smoothing (FACET), and median filtering (MEDIAN). The evaluation procedure involves two steps. First, the image is partitioned into regions based on the amount of spatial activity in a neighborhood of a pixel, where spatial activity is defined as local gradient. In the second part of the procedure an objective measure, the mean-square error, for each region of the partitioned image is obtained to evaluate the performance of the smoothing scheme at the corresponding level of spatial activity content. This evaluation procedure provides a convenient way to compare both the edge-preserving and noise-smoothing abilities of different schemes. The smoothing schemes were tested on a specially generated image with varying degrees of added noise and different edge slopes. The results of the comparison study are presented.