Description: The research Seminar on Image Processing – Pattern Matching comments on image processing and how pattern matching is done during image processing. Wherein number of calculations for a normalized correlation factor can be reduced thus increasing the speed and processing of pattern matching in digital image processing. In the pattern matching processing when an insensitive region is set in a template image, values (the sum and the squared sum) obtained during a previous operation for a prior search target sub-image are employed to perform calculations for a current search target sub-image , relative to coordinate sequence code that indicates the start point and the end point of a sequence of pixels having values of “1.”
What is pattern matching:
The research paper suggests that pattern matching is the method of checking the constituents within a given pattern. In contrast to pattern recognition. This method facilitates easy specification of a pattern. In pattern matching there are either sequences or tree structures. Pattern matching is used to test whether things have a desired structure, to find relevant structure, to retrieve the aligning parts, and to substitute the matching part with something else.
The research paper suggests a point that pattern matching is a powerful tool for syntax analysis. The main idea of pattern matching comes from the SNOBOL4 language (see the wonderful book THE SNOBOL4 PROGRAMMING LANGUAGE by R. E. Griswold, J. F. Poage and I. P. Polonsky). Some of the pattern expression atoms and statements were taken from there. One can find that patterns are very similar to the Backus-Naur forms. Comparing with the regular expressions (used by grep and egrep in UNIX) patterns are more powerful, but slower in matching.
Conclusion: The research paper concludes on a note that pattern matching is a perfect tool invented for image processing. The practical benefits of the tool are many.
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