The invention discloses an
infrared face identification method based on a local parallel
nerve network. A
network structure mainly comprises four portions and the method is characterized by 1, extracting a preliminary
convolution characteristic: through one group of 2*2
convolution kernel, extracting a preliminary face characteristic and arranging an output characteristic
signal; 2, generating a parallel multi-scale
convolution characteristic: using a parallel multi-scale convolution
network structure to extract face characteristics representing different scale information; 3, generating a classification characteristic vector: using a fully-connected layer to integrate the convolution characteristic so as to acquire a characteristic vector which is used to finally represent a
face identity and is used for classification input, and carrying out modified linear activation and random
neglect processing; and 4, training and testing a classifier: inputting a processed fully-connected characteristic vector into a Softmax classifier and calculating losses, and reversely spreading, training and adjusting a
network parameter so as to realize
infrared face identification. The method can be widely applied to
infrared face identification and identity identification applications.