An Improved Scale Invariant Feature Transform Algorithm Based on Weighted Principal Component Analysis for Image Matching

摘要：

　　Since first proposed,SIFT (Scale Invariant Feature Transform) has attracted great attention in the field of computer vision because of many of its advantages.In the paper,we propose a novel SIFT algorithm based on Weighted-PCA.Besides,in order to improve the matching accuracy,we redefine the distance measurement in the matching process.The experimental results show that the proposed method is more effective than existing ones under image rotation,scale transformation and noise degradation.

关键词： Scale Invariant Feature Transform Weight Principal Component Analysis Images Matching

作者: Qianxi Guo Huiyuan Wang Yongwei Zheng

作者单位: School of Information Science and Engineering, Shandong University, Jinan, China

会议类型: 国际会议

会议名称: 2012 IEEE 11th International Conference on Signal Processing (第11届IEEE信号处理国际会议)

会议地点: 北京

会议语种:英文

页码: 1106-1109

在线出版日期: 2012-10-21（万方平台首次上网日期，不代表论文的发表时间）