Paper
6 October 1998 Automated generation of efficient code for gray-scale image processing
Author Affiliations +
Proceedings Volume 3521, Machine Vision Systems for Inspection and Metrology VII; (1998) https://doi.org/10.1117/12.326971
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Abstract
The SKIPSM (Separated-Kernel Image Processing using finite- State Machines) paradigm has been extended with excellent results to grey-scale morphology with arbitrary flat structuring elements. But casual users can not be expected to master the techniques for creating SKIPSM implementations for user-specified SEs, thus limiting the usefulness of the technique. This paper addresses that limitation by providing a completely automated procedure for generating the SKIPSM implementation for a wide range of grey-scale image processing operations in addition to grey-scale morphology, given only the definition of the neighborhood over which the computations are to be made. These neighborhoods need not be square or rectangular, but can be made up of arbitrary collections of contiguous or non-contiguous pixels. Examples of the operations that can be performed include grey-scale dilation and erosion with flat structuring elements, area sum or arithmetic mean, geometric mean, etc. In effect, this paper provides the basic structure for a computer program to write efficient computer code in a target language such as C. This code-generating program could be written in almost any computer language, but because it involves both list processing and some backtracking. Prolog would be an excellent choice. This technique can be extended to three- and higher-dimensional grey-scale morphology without great difficulty.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frederick M. Waltz "Automated generation of efficient code for gray-scale image processing", Proc. SPIE 3521, Machine Vision Systems for Inspection and Metrology VII, (6 October 1998); https://doi.org/10.1117/12.326971
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KEYWORDS
Image processing

Remote sensing

Software

Binary data

Computer simulations

Selenium

Computer programming languages

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