Title :
An improved minimum spanning tree stereo matching algorithm
Author :
Zhigang Liu ; Keyu Li ; Xiaoxue Zhang
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
The minimum spanning tree stereo matching algorithm only takes one channel of R, G, B channels into account, ignoring the effect of the other two channels on the final edge weight in color image. This paper proposes an improved minimum spanning tree stereo matching algorithm, which calculates the weighted euclidean distance using a three-channel approach, and combines three-channel edge weight. This algorithm has been tested on Tsukuba, Venus, Teddy, Cones image. Simulation results show that the improved algorithm enhances the robustness of edge weight function and the connectivity of minimum spanning tree. It not only improves stereo matching accuracy, but also increases computational speed.
Keywords :
edge detection; image colour analysis; image matching; stereo image processing; trees (mathematics); R-G-B channels; Tsukuba Venus Teddy Cones image; color image; edge weight function robustness; minimum spanning tree connectivity; minimum spanning tree stereo matching algorithm; three-channel edge weight; weighted Euclidean distance; Accuracy; Algorithm design and analysis; Color; Image edge detection; Runtime; Standards; Venus; Binocular Vision; Minimum Spanning Tree; Stereo Matching;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162223