False Match Elimination for Face Recognition Based on SIFT Algorithm

摘要：

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.

关键词： false match elimination SIFT face recognition PROSAC

作者: Xuyuan Gu Ping Shi Meide Shao

作者单位: Information Engineering School Communication University of China Beijing, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 550-555

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）