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Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05)
Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks
Dalian, China
December 05-December 08
ISBN: 0-7695-2405-2
| ASCII Text | x | ||
| Xijun Hua, Masahiro Yokomichi, Michio Kono, "Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks," Parallel and Distributed Computing Applications and Technologies, International Conference on, pp. 856-860, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005. | |||
| BibTex | x | ||
| @article{ 10.1109/PDCAT.2005.227, author = {Xijun Hua and Masahiro Yokomichi and Michio Kono}, title = {Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks}, journal ={Parallel and Distributed Computing Applications and Technologies, International Conference on}, volume = {0}, year = {2005}, isbn = {0-7695-2405-2}, pages = {856-860}, doi = {http://doi.ieeecomputersociety.org/10.1109/PDCAT.2005.227}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Parallel and Distributed Computing Applications and Technologies, International Conference on TI - Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks SN - 0-7695-2405-2 SP856 EP860 A1 - Xijun Hua, A1 - Masahiro Yokomichi, A1 - Michio Kono, PY - 2005 KW - null VL - 0 JA - Parallel and Distributed Computing Applications and Technologies, International Conference on ER - | |||
In the literature, most of the stereo matching methods have been limited to gray level images, only few authors have dealt with color images straightly. In this paper, we propose a novel area-based color stereo matching method based on competitive-cooperative neural networks. Seven kinds of color spaces are tested in order to evaluate their suitability to stereo matching. The experimental results show that the matching precision is increased efficiently, when using adaptive color features instead of gray values.According to the experimental results, Ohta, Opponent and YCbCr color spaces can offer good color features for stereo matching.
Citation:
Xijun Hua, Masahiro Yokomichi, Michio Kono, "Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks," pdcat, pp.856-860, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005
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