关键词: 人脸验证, 尺度不变特征（SIFT）, 数量特征, 位置特征

Abstract: The face verification is the branch of face recognition, and it is the research hotspot in criminal investigation. According to the characteristics of face verification, the Scale-Invariant Feature Transform（SIFT） algorithm is used, at the same time the image blocking method is combined to divide the SIFT features into number features and position features, thus the goal of face verification can be achieved. Firstly, the image registration is applied, then SIFT algorithm is used to find the matching feature points. Secondly, the images are blocked into several blocks, and the feature points are calculated in each block to achieve the feature vector. Lastly, the number of feature points is computed. If it reaches the preset threshold, the similarity of the matching vector is calculated. Otherwise, if any of the conditions is not satisfied, the images are defined as a non-verification pair. CAS and FERET databases are used to test the algorithm, and the false alarm rate is 19%, while the missing alarm rate is 0.3%. The experimental results show that the proposed algorithm is a new effective way in face verification. This method can be used in face verification after optimization.

Key words: face verification, Scale-Invariant Feature Transform（SIFT）, number features, position features