Statistical pattern recognition using the Normalized Complex Moment Components vector

Paschalakis, Stavros and Lee, Peter (2000) Statistical pattern recognition using the Normalized Complex Moment Components vector. Advances in Pattern Recognition , 1876 . pp. 532-539. ISSN 0302-9743 . (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1007/3-540-44522-6_55

Abstract

This paper presents a new feature vector for statistical pattern recognition based on the theory of moments, namely the Normalized Complex Moment Components (NCMC). The NCMC will be evaluated in the recognition of objects which share identical silhouettes using grayscale images and its performance will be compared with that of a commonly used moment based feature vector, the Hu moment invariants. The tolerance of the NCMC to random noise and the effect of using different orders of moments in its calculation will also be investigated.

Item Type: Article
Additional information: Joint International-Association-of-Pattern-Recognition International Workshops - SSPR 2000 and SPR 2000 Univ Alicante, Alicante, Spain Aug 30-SEP 01, 2000 Int Assoc Pattern Recognit; Univ Valencia, Dept Informat
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: A. Xie
Date Deposited: 28 Aug 2009 14:25
Last Modified: 02 May 2014 13:33
Resource URI: http://kar.kent.ac.uk/id/eprint/16478 (The current URI for this page, for reference purposes)
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