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Proceedings Paper

Comparative study of moment invariants for perspective transformation
Author(s): Shan Yu; Adam Klette; Charles Olinger; Ernest L. Hall
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Paper Abstract

Various moment invariants have been developed for object recognition applications. In this paper, we conduct a comparative study of different moment invariants with respect to perspective transformation. Perspective transformations are induced by the lens of the human eye or an optical system. A physical model of the perspective transformation is given. concepts of Zernike moments and regular moments are discussed and their derivation compared. Their corresponding rotational, scale, and translational invariance properties are presented. A group of quadratic form perspective moment invariants is also introduced. Comparisons and estimations are made on the performance and properties of these invariants in object recognition from both a theoretical and a computational point of view. After the overall estimation, it is shown that the most effective way in recognizing object under perspective transformation is to use quadratic form invariants.

Paper Details

Date Published: 1 November 1992
PDF: 10 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131519
Show Author Affiliations
Shan Yu, Univ. of Cincinnati (United States)
Adam Klette, Monarch Foundation (United States)
Charles Olinger, Monarch Foundation (United States)
Ernest L. Hall, Univ. of Cincinnati (United States)


Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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