Integrating kAS and SIFT-like descriptor for image description

Mianyou Shang, Jing Pan, Yanwei Pang, Yuan Yuan

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Shape-descriptor (e.g. Adjacent Contour Segments, i.e. kAS) and keypoint-descriptor (e.g. Scale Invariant Feature Transform, i.e. SIFT) are widely used for computer vision. However, few works principally integrate shape-descriptor and keypoint-descriptor to describe the content of an image. On one hand, in some cases the degree of locality of keypiont-descriptor is too high to capture semantic characteristics of an object. On the other hand, though the shape has higher semantic level than keypoint, it contains no texture information because only the information of contour/edge is used. To make full use of the information of both shape and keypoint for generate robust and distinctive features, in this paper we propose an algorithm to integrate shape and keypoint descriptor. Specifically, we employ kAS to extract useful shape information. Then keypoints of a kAS shape are defined at which we propose to extract SIFT-like features. Experimental results on image matching demonstrate the effectiveness of the proposed algorithm.

源语言英语
主期刊名Proceedings - 6th International Conference on Image and Graphics, ICIG 2011
533-537
页数5
DOI
出版状态已出版 - 2011
已对外发布
活动6th International Conference on Image and Graphics, ICIG 2011 - Hefei, Anhui, 中国
期限: 12 8月 201115 8月 2011

出版系列

姓名Proceedings - 6th International Conference on Image and Graphics, ICIG 2011

会议

会议6th International Conference on Image and Graphics, ICIG 2011
国家/地区中国
Hefei, Anhui
时期12/08/1115/08/11

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