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Optical Engineering

Noncentral image moments for invariant pattern recognition
Author(s): Lixin Shen; Yunlong Sheng
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Paper Abstract

When invariant moments are used as numerical features for image description and recognition, the noncentral moments generated by correlation can be used for scale, rotation, and shift-invariant pattern recognition. A search in the feature-vector space for matching the input and reference feature vectors can be fast. The new method can apply to multiple-image input without segmentation of the images, and the noncentral moments are more robust than the central moments to noise.

Paper Details

Date Published: 1 November 1995
PDF: 6 pages
Opt. Eng. 34(11) doi: 10.1117/12.213614
Published in: Optical Engineering Volume 34, Issue 11
Show Author Affiliations
Lixin Shen, Univ. Laval (Canada)
Yunlong Sheng, Univ. Laval (Canada)


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