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Proceedings Paper

Object detection by radial basis neural network filtering of spectral data
Author(s): Tom G. Thomas Jr.; M. Serkan Ozkan; Ye Tung; Mohammad Alam
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Paper Abstract

An object recognition technique has been developed that allows the rapid screening of multispectral images for objects with known spectral signatures. The technique is based on the configuration of a radial basis neural network (RBN) that is specific for a particular object spectral signature or series of object spectral signatures. The method has been used to identify features in CASI-2 and HYDICE images with results comparable to conventional spatial object recognition techniques with a significant reduction in processing time. Radial basis neural networks have several advantages over the more common backpropagation neural networks, including better selectivity and faster training, resulting in a significant reduction in overall image processing time and greater accuracy.

Paper Details

Date Published: 24 August 2006
PDF: 12 pages
Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 631204 (24 August 2006); doi: 10.1117/12.677931
Show Author Affiliations
Tom G. Thomas Jr., Univ. of South Alabama (United States)
M. Serkan Ozkan, Univ. of South Alabama (United States)
Ye Tung, Univ. of South Alabama (United States)
Mohammad Alam, Univ. of South Alabama (United States)

Published in SPIE Proceedings Vol. 6312:
Applications of Digital Image Processing XXIX
Andrew G. Tescher, Editor(s)

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