分块LBP的素描人脸识别

The sketch face recognition combining with Ada Boost and blocking LBP

目的素描人脸识别属于异质人脸识别范畴,是刑侦领域的研究热点。根据素描人脸识别的特点,采用分块局部二值模式(LBP)特征,并用Ada Boost算法提取能有效鉴别素描人脸图像和可见光人脸图像对应关系的特征块。方法对素描图像和可见光图像配准后,进行分块处理,计算每块的LBP直方图,将LBP直方图作为Ada Boost待选择特征。计算素描图像子块与可见光图像子块之间的Log概率统计,利用Ada Boost算法进行特征提取,逐步挑选能有效识别的特征子块,并把这些优选特征子块用于未知素描人脸识别。结果利用现有的素描人脸库,分别进行非交叉和交叉实验验证,识别率分别达到99%以及100%,证明了本文算法的有效性。结论该算法经优化后,可用于素描人脸识别。

Objective 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. Method After registering the sketch image and visible image, the image is blocked, and the LBP his- togram of each block is calculated. This LBP histogram is used to select the features of each block. The log probability sta- tistics 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. Result 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. Conclusion This method can be used in sketch face recognition after optimization.