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Proceedings Paper

Texture Based Image Analysis With Neural Nets
Author(s): Irina Ilovici; Hoo-Tee Ong; Kim Ostrander
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Paper Abstract

In this paper, we combine direct image statistics and spatial frequency domain techniques with a neural net model to analyze texture based images. The resultant optimal texture features obtained from the direct and transformed image form the exemplar pattern of the neural net. The proposed approach introduces an automated texture analysis applied to metallography for determining the cooling rate and mechanical working of the materials. The results suggest that the proposed method enhances the practical applications of neural nets and texture extraction features.

Paper Details

Date Published: 1 March 1990
PDF: 8 pages
Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969780
Show Author Affiliations
Irina Ilovici, The Hartford Graduate Center (United States)
Hoo-Tee Ong, The Hartford Graduate Center (United States)
Kim Ostrander, The Hartford Graduate Center (United States)


Published in SPIE Proceedings Vol. 1192:
Intelligent Robots and Computer Vision VIII: Algorithms and Techniques
David P. Casasent, Editor(s)

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