Sketch Face Recognition: P-HOG Multi-Features Fusion

With the development of biometric recognition technology, sketch face recognition has been widely applied to assist the police to confirm the identity of the criminal suspect. Most of the present recognition methods use the image features directly, in which the key parts can’t be used sufficiently. This paper presents a sketch face recognition method based on P-HOG multi-features weighted fusion. Firstly, the global face image and the local face image which contains key components of the face are divided into patches based on spatial scale pyramid, and then the global P-HOG features and local P-HOG features are extracted, respectively. After that, the dimensions of global and local features are reduced using PCA and NLDA. Finally, the features are weighted based on sensitivity and fused. The nearest neighbor classifier is used to complete the final recognition. The experimental results on different databases show that the proposed method outperforms state-of-the-art methods.