Adaptive Gabor Wavelet for Efficient Object Recognition

This paper describes, using situational awareness and Genetic algorithm, a run-time optimization methodology of the Gabor wavelet parameters so that it produces a feature space for efficient object recognition. Gabor wavelet efficiently extracts the feature space of orientation selectivity, spatial...

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Bibliographic Details
Published inKnowledge-Based Intelligent Information and Engineering Systems pp. 308 - 318
Main Authors Jeon, In Ja, Nam, Mi Young, Rhee, Phill Kyu
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
SeriesLecture Notes in Computer Science
Subjects
Face Recognition
Gabor Wavelet
Object Recognition
Recognition Rate
Situational Awareness
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Summary:This paper describes, using situational awareness and Genetic algorithm, a run-time optimization methodology of the Gabor wavelet parameters so that it produces a feature space for efficient object recognition. Gabor wavelet efficiently extracts the feature space of orientation selectivity, spatial frequency and spatial localization. Most previous object recognition approaches using Gabor wavelet do not include systematic optimization of the parameters for the Gabor kernel, even though the system performance might be much sensitive to the characteristics of the Gabor parameters. This paper explores efficient object recognition using adaptive Gabor wavelet based situational aware method. The superiority of the proposed system is shown using IT-Lab, FERET and Yale face database. We achieved encouraging experimental results.
ISBN:3540288953
9783540288954
ISSN:0302-9743
1611-3349
DOI:10.1007/11552451_41