Network Crime Information Retrieval Framework based on Facial Image Recognition

Network crime information retrieval framework based on facial image recognition is designed in this article. Due to the intelligence and professionalism of crime methods, the variety of criminal methods, and the high degree of concealment of crimes, the detection of cybercrime is much more difficult than traditional cases, which brings great difficulty to the investigation of the case which leads to the detection with low rate. The face analytic model is used to construct the efficient crime data modelling system. The regular term of the ideal coding coefficient matrix is introduced to represent the coefficients of samples for the same types which are as close as possible. The representation coefficients of samples of different types are as different as possible, which also increases the discrimination of coding coefficients. The comprehensive analysis of the model is tested and compared with the state-of-the-art methodologies. The experiment shows the detection accuracy has been improved to 98.77%.