Discrimination of natural contours by means of time-scale-frequency decompositions

Authors:
Leandro A. Loss;Clésio L. Tozzi
Affiliations:
Department of Computer Science and Engineering, School of Electrical and Computer Engineering, State University of Campinas;Department of Computer Science and Engineering, School of Electrical and Computer Engineering, State University of Campinas
Venue:
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Year:
2005

Citing 2
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The multiresolution fourier transform: a general purpose tool for image analysis

The multiresolution fourier transform: a general purpose tool for image analysis

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Abstract

This paper evaluates the discriminative potential of time-scale-frequency decompositions for contour-based recognition of natural shapes. Specifically, it provides the analysis and comparison of descriptors derived from the Fourier Transform, the Short-Time Fourier Transform, the Wavelet Transform and the Multi-Resolution Fourier Transform. Linear Discriminant Analysis and Backward Sequential Selection are employed for dimensionality reduction and selection of the most significant features, respectively. A Bayesian Classifier is used for class discrimination. To improve discrimination, a hierarchical classification is adopted. The approaches are analyzed and compared considering experiments developed over digitalized leaves.