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Image matching algorithm with color information based on SIFT
Yu, Xiaoyong1,2; Lei, Hao1,3; Du, Yunfei1,2; Li, Baopeng1; Yuan, Xiaobin1; Gao, Wei1; Song, Zongxi1; Zheng, Peiyun1
2018
会议名称10th International Conference on Digital Image Processing, ICDIP 2018
会议录名称Tenth International Conference on Digital Image Processing, ICDIP 2018
卷号10806
会议日期2018-05-11
会议地点Shanghai, China
出版者SPIE
产权排序1
摘要Image matching is an important topic in the field of computer vision, in view of high robustness and accuracy, SIFT or the improved methods based on SIFT is generally used for image matching algorithms. The traditional SIFT method is implemented on grayscale images without regard to the color information of images, which may cause decreasing of the matching points and reduction of the matching accuracy. Prevailing color descriptors can effectively add color information into SIFT, however dramatically increase the complexity of algorithm. In this paper, a novel approach is proposed to take advantage of the color information for image matching based on SIFT. The proposed algorithm uses the gradient information of color channel as the compensation of luminance channel, which can effectively enhance the color information with SIFT. Experimental results show that the number of feature points and matching accuracy can be significantly promoted, while the complexity and performance of image matching algorithm are well trade-off. © 2018 SPIE.
作者部门空间光学应用研究室
DOI10.1117/12.2502820
收录类别EI
ISBN号9781510621992
语种英语
ISSN号0277786X
EI入藏号20183605779155
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30600
专题空间光学应用研究室
通讯作者Du, Yunfei
作者单位1.Space Optics Lab, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Science, Xi'an; 710019, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China;
3.Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Science, Beijing; 100190, China
推荐引用方式
GB/T 7714
Yu, Xiaoyong,Lei, Hao,Du, Yunfei,et al. Image matching algorithm with color information based on SIFT[C]:SPIE,2018.
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