Optimal waveform representation of shape and texture features for image classification

Arturo S. Dimalanta; Keith L. Phillips

doi:10.1117/12.279687

30 October 1997 Optimal waveform representation of shape and texture features for image classification

Arturo S. Dimalanta, Keith L. Phillips

Proceedings Volume 3169, Wavelet Applications in Signal and Image Processing V; (1997) https://doi.org/10.1117/12.279687
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

The problem of image feature extraction for classification is difficult because of the high dimensionality inherent in image data. By extracting only relevant image features we reduce the dimensionality of the problem and improve classification accuracy. We further enhance classification performance by finding an optimal representation of the extracted image features which maximizes separability distance among classes. The principal tools used are Fourier series, wavelet packets, local discriminant basis analysis, and neural networks.

Citation Download Citation

Arturo S. Dimalanta and Keith L. Phillips "Optimal waveform representation of shape and texture features for image classification", Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); https://doi.org/10.1117/12.279687

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