2014
DOI: 10.1007/978-3-319-07998-1_51
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Image Classification Using Separable Discrete Moments of Charlier-Tchebichef

Abstract: In this paper, we propose a new set of Charlier-Tchebichef invariant moments. This set is derived algebraically from the geometric invariant moments. The presented approach is tested in several well known computer vision datasets including moment's invariability and classification of objects. The performance of these invariant moments used as pattern features for a pattern classification is compared with Tchebichef-Krawtchouk, Tchebichef-Hahn and Krawtchouk-Hahn invariant moments.

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Cited by 5 publications
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References 21 publications
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