A comprehensive survey of thinning methodologies is presented. A wide range of thinning algorithms, including iterative deletion of pixels and nonpixel-based methods, is covered. Skeletonization algorithms based on medial axis and other distance transforms are not considered. An overview of the iterative thinning process and the pixel-deletion criteria needed to preserve the connectivity of the image pattern is given first. Thinning algorithms are then considered in terms of these criteria and their modes of operation. Nonpixel-based methods that usually produce a center line of the pattern directly in one pass without examining all the individual pixels are discussed. The algorithms are considered in great detail and scope, and the relationships among them are explored. >

Thinning methodologies-a comprehensive survey

Networks of constraints: Fundamental properties and applications to picture processing

Research and development of OCR systems are considered from a historical point of view. The historical development of commercial systems is included. Both template matching and structure analysis approaches to R&D are considered. It is noted that the two approaches are coming closer and tending to merge. Commercial products are divided into three generations, for each of which some representative OCR systems are chosen and described in some detail. Some comments are made on recent techniques applied to OCR, such as expert systems and neural networks, and some open problems are indicated. The authors' views and hopes regarding future trends are presented. >

Historical review of OCR research and development

Simple sets of parallel operations are described which can be used to detect texture edges, "spots," and "streaks" in digitized pictures. It is shown that, by comparing the outputs of the operations corresponding to (e.g.,) edges of different sizes, one can construct a composite output in which edges between differently textured regions are detected, and isolated objects are also detected, but the objects composing the textures are ignored. Relationships between this class of picture processing operations and the Gestalt psychologists' laws of pictorial pattern organization are also discussed.

Edge and Curve Detection for Visual Scene Analysis

: The field of picture processing by computer is reviewed from a technique-oriented standpoint. Only the processing of given pictures (as opposed to computer-synthesized pictures) is considered. Specific areas covered include: (a) Pictures as information sources and their efficient encoding; (b) Approximation of pictures - sampling and quantization techniques; (c) Position-invariant operations on pictures and their implementation (digital, electro-optical, optical); applications to matched filtering (template matching), spatial frequency filtering and image restoration, measurement of image quality, and image enhancement ('smoothing' and 'sharpening'); (d) Picture properties (linear; local and 'textural'; random) useful for pictorial pattern recognition; (e) 'Figure extraction' from pictures; figure properties (topology, size, shape); (f) Picture description and 'picture languages.' (Author)

Picture processing by computer

This report describes the system design of an all-digital computer for visual recognition. One processor, the Pattern Articulation Unit (PAU), has been singled out for detailed discussion. Other units, in particular the Arithmetic Unit and the Taxicrinic Unit, are treated in reports listed in the bibliography. The PAU has been shown to be a processor of fundamentally new design-its logical organization has no analog in the central processing unit of existing computers. The PAU is the first modular parallel processor which because of its digital organization is capable of more reliable visual identification than part analog/part digital preprocessors of much less generality and potential virtuosity; is faster than any presently suggested alternative realizable today at comparable cost; and can serve as a prototype to a new generation of parallel computers that will capitalize upon thin film and integrated semiconductor circuitry of the immediate future.

The Illinois Pattern Recognition Computer-ILLIAC III

Consistent properties of composite formation under a binary relation

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.

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Bruce H. McCormick

Papers

The Illinois Pattern Recognition Computer-ILLIAC III

Consistent properties of composite formation under a binary relation

Parametric description of a scan-display system