关键词: 尺度不变特征变换, 特征描述子, 余弦相似度, 人脸图像匹配

Abstract:

To solve the problem that face image matching takes a long time and has a low correct rate in complex background such as illumination, posture and expression, a face matching algorithm based on improved SIFT（Scale-Invariant Feature Transform） and Cosine Similarity（CS） is proposed, which constructs the features of circular partition. Descriptor reduces the dimension of eigenvector, uses forward and backward bidirectional matching and the principle of cosine similarity between pairs of matching points in the set to approximately satisfy the cosine similarity, and uses cosine similarity to eliminate mismatching point pairs. Experiments on FEI face database are compared with the popular face matching methods. The experimental results show that the algorithm improves the matching speed by an average of 2~2.5 times on the premise of guaranteeing the correct rate of face matching and the number of matching points.

Key words: Scale-Invariant Feature Transform（SIFT）, feature descriptor, Cosine Similarity（CS）, face image matching