Combined geometric transformation and illumination invariant object recognition in RGB color images

Paschalakis, S. and Lee, P. (2000) Combined geometric transformation and illumination invariant object recognition in RGB color images. In: 15th International Conference on Pattern Recognition (ICPR-2000), Sep 03-07 2000, Barcelona, Spain. (The full text of this publication is not available from this repository)

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Abstract

This paper presents a novel approach for object recognition in RGB color images using features based on the theories of geometry ic and complex moments. BI effectively combining the properties of the RGB color space and the normalization procedures and properties of the geometric and complex moments we have implemented a feature vector that is invariant to geometric transformations (i.e. translation, rotation and scale) and changes in both the illumination color and illumination intensity The experimental results presented here will demonstrate the performance of the proposed feature set and investigate ifs tolerance to image distortions.

Item Type: Conference or workshop item (Paper)
Additional information: Int Assoc Pattern Recognit; Assoc Pattern Recognit & Image Anal; Ctr Visio Comp; Univ Autonoma Barcelona; Univ Politecn Catalunya; Comissionat Universitats Recerca, Generalitat Catalunya Dept Presidencia; Minist Ciencia Tecnol; Fdn Catalana Recerca; HP Invent
Subjects: T Technology
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: A. Xie
Date Deposited: 28 Aug 2009 13:56
Last Modified: 27 Jun 2012 09:41
Resource URI: http://kar.kent.ac.uk/id/eprint/16475 (The current URI for this page, for reference purposes)
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