Share Email Print

Proceedings Paper

Optimal waveform representation of shape and texture features for image classification
Author(s): Arturo S. Dimalanta; Keith L. Phillips
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 30 October 1997
PDF: 11 pages
Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); doi: 10.1117/12.279687
Show Author Affiliations
Arturo S. Dimalanta, Univ. of Colorado/Colorado Springs (United States)
Keith L. Phillips, Univ. of Colorado/Colorado Springs (United States)

Published in SPIE Proceedings Vol. 3169:
Wavelet Applications in Signal and Image Processing V
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?