SAMME.RCW algorithm based face recognition optimization method

The invention relates to a SAMME.RCW algorithm based face recognition optimization method, which comprises the steps of firstly carrying out feature extraction on a face image, and carrying out recognition classification by using an image feature vector according to a SAMME.RCW algorithm. Modification is carried out on a weight adjustment process of the SAMME.RCW algorithm, thereby ensuring the weight of every class of samples not to be too small when re-sampling occurs, also enabling weight adjustment after re-sampling to be more partial to minority-class samples, and ensuring classification effects of the samples. A requirement of the SAMME.RCW algorithm for the performance of a weak classifier is that the weight of correctly classified samples in each class is greater than the weight of any other class of samples, and a requirement for the accuracy is performed on each class independently. Through modification carried out on weight allocation in re-sampling, the probability of being selected of each class