Paper
30 April 1987 Advanced Image-Processing Architectures For Machine Vision
Robert M. Lougheed
Author Affiliations +
Abstract
A large number of computer system designs for image analysis have been proposed, and many have been or are being constructed. Although many of them share similar features, the use of proprietary terminology and lack of detailed standardized processing examples in descriptive documentation makes understanding and comparison difficult. Consequently, the a priori estimation of algorithm performance on a given system becomes a combination of ad hoc guesses and somewhat idealized extrapolation. Also, in concentrating on only a portion of the overall data flow, many of these designs have optimized only a part of the system and have reduced the overall price/performance ratio. This paper identifies the fundamentally distinct primitive types of image transformations used in image processing and discusses the characteristics of typical applications and missions. Next, a taxonomy of architectures is presented which enables the various approaches to be unambiguously categorized and evaluated. Several existing designs are used as examples, and the relative merits of each are discussed.
© (1987) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert M. Lougheed "Advanced Image-Processing Architectures For Machine Vision", Proc. SPIE 0755, Image Pattern Recognition: Algorithm Implementations, Techniques, and Technology, (30 April 1987); https://doi.org/10.1117/12.940004
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Image processing

Machine vision

Data processing

Detection and tracking algorithms

Pattern recognition

Image segmentation

Raster graphics

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