The invention discloses a selective integrated face recognition method based on genetic algorithm fusion differential evolution. Firstly, the HOG feature of the face image is extracted, and then the PCA algorithm is used to reduce the dimension of the face image, so as to reduce the computational complexity. Finally, use After dimensionality reduction, the GADESEN algorithm is used to classify and identify the data. This method takes the support vector machine as the base classifier, extracts N samples from the original training set with replacement, iterates T times according to this method, and uses the sample set generated each time to train the base classifier model. The classifier encodes real numbers to generate an initial population. In the mutation operation, the difference vector is used to guide the mutation and then produce high-quality individuals. The crossover operation uses the parent individual and the mutant individual to generate crossover individuals, which increases the diversity of individuals. Retention strategies for genetic evolution.