DocumentCode :
1852144
Title :
Color stereo matching based on self-organization neural networks
Author :
Hua, Xijun ; Yokomichi, Masahiro ; Kono, Michio
Author_Institution :
Dept. of Comput. Sci. & Syst. of Eng., Miyazaki Univ., Japan
Volume :
1
fYear :
2004
fDate :
25-28 July 2004
Abstract :
Stereo matching is the key issue of stereo vision. In the literature, most of the stereo matching algorithms have been limited to gray level images. In this paper, we propose a new color stereo matching approach based on self-organization neural networks. For the real images, we propose a segmentation method to deal with the initial similarity map. The final similarity map is established by taking logical AND calculation of different color feature similarities so as to make full use of the color information. Experimental results have shown that the quality of the stereo matching can be considerably improved by using appropriate color matching algorithm comparing with the conventional gray value algorithm.
Keywords :
feature extraction; image colour analysis; image matching; image segmentation; self-organising feature maps; stereo image processing; color feature similarities; color matching algorithm; color stereo matching algorithm; gray level images; image segmentation method; logical AND calculation; self-organization neural networks; stereo vision; Color; Computer science; Image reconstruction; Image segmentation; Neural networks; Neurons; Object recognition; Pixel; Stereo vision; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2004. MWSCAS '04. The 2004 47th Midwest Symposium on
Print_ISBN :
0-7803-8346-X
Type :
conf
DOI :
10.1109/MWSCAS.2004.1353935
Filename :
1353935
Link To Document :
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