Sketch face recognition

which belongs to heterogeneous face recognition

is a difficult research area in criminal investigation. Blocking local binary pattern (LBP) features are used according to the characteristics of sketch face recognition

and the features that can discriminate the sketch face image and visible face image are extracted by using AdaBoost algorithm. After registering the sketch image and visible image

the image is blocked

and the LBP histogram of each block is calculated. This LBP histogram is used to select the features of each block. The log probability statistics of the sketch and visible images is calculated

and features are extracted by using AdaBoost algorithm. Features that can recognize effectively are chosen step by step and are used in unknown sketch face recognition. Crossover and non-crossover experiments are tested by using the existing sketch database

and the recognition rates are 99% and 100%

respectively. Results prove that the proposed algorithm is an effective sketch face recognition approach. This method can be used in sketch face recognition after optimization.