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Proceedings Paper

Scale- and rotation-invariant pattern recognition by a rotating kernel min-max transformation
Author(s): Yim-Kul Lee; William T. Rhodes
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Paper Abstract

A new hybrid optical/digital method for scale- and rotation-invariant pattern recognition is presented using a rotating kernel mm-max transformation. In this method, the input object is convolved with a long, narrow 2-D kernel. As the kernel rotates, the convolution output is monitored and the maximum [=Maxl and minimum [=MinJ values, along with the angle °M at which Max is found, are stored. The processed object is given by some function f[ , I of Max and Mm values. From the description (f[ , , OM), the 9-projection is first calculated. To obtain scale invariance, this projection is normalized by its integral. The normalized 0-projection exhibits an approximate scale invariance, the recognition capability depending to a small degree on the kernel length used. Since the kernel rotates, rotation invariance is achieved. Results of numerical experiments are presented. Some effects that variations in the kernel length have on the discrimination of objects are discussed.

Paper Details

Date Published: 27 December 1990
PDF: 10 pages
Proc. SPIE 1347, Optical Information Processing Systems and Architectures II, (27 December 1990); doi: 10.1117/12.23404
Show Author Affiliations
Yim-Kul Lee, Georgia Institute of Technology (United States)
William T. Rhodes, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1347:
Optical Information Processing Systems and Architectures II
Bahram Javidi, Editor(s)

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