Scale- and rotation-invariant pattern recognition by a rotating kernel min-max transformation

Yim-Kul Lee; William T. Rhodes

doi:10.1117/12.23404

27 December 1990 Scale- and rotation-invariant pattern recognition by a rotating kernel min-max transformation

Yim-Kul Lee, William T. Rhodes

Proceedings Volume 1347, Optical Information Processing Systems and Architectures II; (1990) https://doi.org/10.1117/12.23404
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

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.

Citation Download Citation

Yim-Kul Lee and William T. Rhodes "Scale- and rotation-invariant pattern recognition by a rotating kernel min-max transformation", Proc. SPIE 1347, Optical Information Processing Systems and Architectures II, (27 December 1990); https://doi.org/10.1117/12.23404

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