Adaptive parameter filtering strategies for spatial frame sequence modeling

Emerson Prado Lopes

doi:10.1117/12.378870

29 February 2000 Adaptive parameter filtering strategies for spatial frame sequence modeling

Emerson Prado Lopes

Proceedings Volume 3968, High-Speed Imaging and Sequence Analysis II; (2000) https://doi.org/10.1117/12.378870
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

This paper shows the new approach results in analyzing and classifying test images focusing on the differences among the existing spatial frame sequence modelings obtained from each region candidate or class. The used tool combination applied to analyze the classify the mosaic images consists of a bank of Gabor filters for decomposing the image and Gaussian filters for building the multi-resolution image representation on the filter bank outputs, and two classifiers: a Bayesian and a low-resolution Bhattacharyya distance RCE neural network classifiers. The training set of textures consists of Brodatz and synthetic patterns.

Citation Download Citation

Emerson Prado Lopes "Adaptive parameter filtering strategies for spatial frame sequence modeling", Proc. SPIE 3968, High-Speed Imaging and Sequence Analysis II, (29 February 2000); https://doi.org/10.1117/12.378870

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