MODIFIED SIFT DESCRIPTOR FOR IMAGE MATCHING UNDER INTERFERENCE

摘要：

There remain many difficult problems in computer vision research such as object recognition, three dimensional reconstruction, object tracking, etc. And the basis of solving these problems relies on image matching.The Scale Invariant Feature Transform (SIFT) S| algorithm has been widely used for image matching application. The SIFT algorithm can successfully extract the most descriptive feature points in given input images taken under different viewpoints.However, the performance of the original SIFT algorithm degrades under the influence of noise. We propose to modify the SIFT algorithm to produce better invariant feature points for image matching under noise. We also propose to employ the Earth Movers Distance (EMD) as the measurement of similarity between two descriptors. We present extensive experiment results to demonstrate the performance of the proposed methods in image matching under noise.

关键词： Feature points SIFT EMD matching

作者: CHENG-YUAN TANG YI-LEH WU MAW-KAE HOR WEN-HUNG WANG

作者单位: Department of Information Management, Huafan University, Taiwan Dept.of Computer Science and Information Engineering, National Taiwan University of Science and Tech Dept.of Computer Science, National Chengchi University, Taiwan

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3294-3300

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）