6 March 2015 Improved SIFT descriptor applied to stereo image matching
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Proceedings Volume 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation; 94460U (2015) https://doi.org/10.1117/12.2180667
Event: International Symposium on Precision Engineering Measurement and Instrumentation, 2014, Changsha/Zhangjiajie, China
Abstract
Scale Invariant Feature Transform (SIFT) has been proven to perform better on the distinctiveness and robustness than other features. But it cannot satisfy the needs of low contrast images matching and the matching results are sensitive to 3D viewpoint change of camera. In order to improve the performance of SIFT to low contrast images and images with large 3D viewpoint change, a new matching method based on improved SIFT is proposed. First, an adaptive contrast threshold is computed for each initial key point in low contrast image region, which uses pixels in its 9×9 local neighborhood, and then using it to eliminate initial key points in low contrast image region. Second, a new SIFT descriptor with 48 dimensions is computed for each key point. Third, a hierarchical matching method based on epipolar line and differences of key points’ dominate orientation is presented. The experimental results prove that the method can greatly enhance the performance of SIFT to low contrast image matching. Besides, when applying it to stereo images matching with the hierarchical matching method, the correct matches and matching efficiency are greatly enhanced.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luan Zeng, Luan Zeng, You Zhai, You Zhai, Wei Xiong, Wei Xiong, } "Improved SIFT descriptor applied to stereo image matching", Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94460U (6 March 2015); doi: 10.1117/12.2180667; https://doi.org/10.1117/12.2180667
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