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Invariant Feature Extraction and Object Shape Matching Using Gabor Filtering

  • Shu-Kuo Sun 
  • Zen Chen
  • Tsorng-Lin Chia 
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2314)

Abstract

Gabor filter-based feature extraction and its use in object shape matching are addressed. For the feature extraction multi-scale Gabor filters are used. From the analysis of the properties of the Gabor-filtered image, we know isolated dominant points generally exist on the object contour, when the filter design parameters are properly selected. The dominant points thus extracted are robust to the image noise, scaling, rotation, translation, and the minor projection deformation. Object shape matching in terms of a two-stage point matching is presented. First, a feature vector representation of the dominant point is used for initial matching. Secondly, the compatibility constraints on the distances and angles between point pairs are used for the final matching. Computer simulations with synthetic and real object images are included to show the feasibility of the proposed method.

Keywords

Gabor Filter Gabor Wavelet Compatibility Constraint Gabor Function Object Contour 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Shu-Kuo Sun 
    • 1
  • Zen Chen
    • 1
  • Tsorng-Lin Chia 
    • 2
  1. 1.Department of Computer Science and Information EngineeringNational Chiao Tung UniversityHinchuTaiwan
  2. 2.Department of Information ManagementMing Chuan UniversityTaoyuanTaiwan

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