Bayesian classification validation scheme driven by a localized/low-resolution Bhattacharyya distance classifier

Emerson Prado Lopes

doi:10.1117/12.351320

25 June 1999 Bayesian classification validation scheme driven by a localized/low-resolution Bhattacharyya distance classifier

Emerson Prado Lopes

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Proceedings Volume 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems; (1999) https://doi.org/10.1117/12.351320
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

A scheme for comparative performance analysis of the Bayesian and the Bhattacharyya distance RCE neural network classifiers is presented. The experiments are performed on synthetic and Brodatz textures. The introduction of the new classifier aims at obtaining a better performance in classifying non-stationary multi-texture images. The two classification schemes are assessed on their localized data representation regarding the ability of extracting non- stationary information from the image. Low-resolution data representation is used to reduce the instability produced with the search for a better trade-off between accuracy and spatial classification performances.

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Emerson Prado Lopes "Bayesian classification validation scheme driven by a localized/low-resolution Bhattacharyya distance classifier", Proc. SPIE 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems, (25 June 1999); https://doi.org/10.1117/12.351320

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KEYWORDS

Image classification

Neural networks

Matrices

Feature extraction

Image filtering

Gaussian filters

Image processing

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