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Proceedings Paper

Stereo matching algorithm based on double components model
Author(s): Xiao Zhou; Kejun Ou; Jianxin Zhao; Xingang Mou
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Paper Abstract

The tiny wires are the great threat to the safety of the UAV flight. Because they have only several pixels isolated far from the background, while most of the existing stereo matching methods require a certain area of the support region to improve the robustness, or assume the depth dependence of the neighboring pixels to meet requirement of global or semi global optimization method. So there will be some false alarms even failures when images contains tiny wires. A new stereo matching algorithm is approved in the paper based on double components model. According to different texture types the input image is decomposed into two independent component images. One contains only sparse wire texture image and another contains all remaining parts. Different matching schemes are adopted for each component image pairs. Experiment proved that the algorithm can effectively calculate the depth image of complex scene of patrol UAV, which can detect tiny wires besides the large size objects. Compared with the current mainstream method it has obvious advantages.

Paper Details

Date Published: 8 March 2018
PDF: 8 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060911 (8 March 2018); doi: 10.1117/12.2285260
Show Author Affiliations
Xiao Zhou, Wuhan Univ. of Technology (China)
Kejun Ou, Wuhan Univ. of Technology (China)
Jianxin Zhao, Wuhan Univ. of Technology (China)
Xingang Mou, Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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