3 October 1995 Application of SKIPSM to binary correlation
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Abstract
Binary correlation is often used for finding specified patterns in complex binary images, especially in industrial inspection tasks such as locating the corners and/or edges of parts. As such, it is an important tool for higher-level 'intelligent' vision systems. Binary correlation is a form of binary template matching which provides a numerical value corresponding to 'degree of fit' rather than an 'all or nothing' answer. Commercially available high-speed image processing systems can readily perform this operation using linear convolvers, but such convolvers are very expensive except for very small kernels. Furthermore, linear convolvers constitute a gross 'overkill' for the relatively simple operation of binary correlation. Specialized binary convolvers have been built, but are not part of standard commercial systems. This paper describes a new pipelined implementation of binary correlation which fits into the standard SKIPSM (separated-kernel image processing using finite state machines) architecture and which can be built using standard ICs costing less than $500 total. The same approach can also be implemented in software, providing an order-of-magnitude increase in speed at no extra cost. Furthermore, this same SKIPSM architecture is highly versatile and programmable, allowing it to be software-reconfigured to perform hundreds of other pipelined image processing operations.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frederick M. Waltz, "Application of SKIPSM to binary correlation", Proc. SPIE 2597, Machine Vision Applications, Architectures, and Systems Integration IV, (3 October 1995); doi: 10.1117/12.223967; https://doi.org/10.1117/12.223967
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