Self-adaptive recognition system based on human face big data artificial intelligence clustering

Abstract

The invention discloses a self-adaptive recognition system based on human face big data artificial intelligence clustering, and belongs to the technical field of information interaction. According tothe invention, the self-adaptive recognition of the human face is achieved through four steps of human face detection, color memory, recognition supervision and unique identification. According to theinvention, when face recognition is carried out, gray scale normalization and black and white normalization of face recognition can be achieved by taking non-negative matrix clustering as a center. According to the invention, when face recognition is carried out, the plane color is fully utilized, and the full-channel saliency map is used as a base point, so that the brightness and color degree of face recognition can be obviously improved. According to the invention, the optimal radiation range of the human face is measured and calculated through the non-negative matrix and iterative computation, an ID with a unique identifier is provided, leakage of personnel information cannot be caused, the privacy of personnel can be effectively protected, and the safety is high. After multiple timesof recognition processing, the system still has high recognition degree, is suitable for most mobile phone systems, forms image and video double-layer protection, and improves the accuracy of face recognition.

Description

technical field [0001] The invention belongs to the field of information interaction technology, and in particular relates to an adaptive recognition system based on human face big data artificial intelligence clustering. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. A series of related technologies that use a video camera or camera to collect images or video streams containing human faces, automatically detect and track human faces in the images, and then perform facial recognition on the detected faces, usually also called portrait recognition and facial recognition. . In general, a face recognition system includes image capture, face location, image preprocessing, and face recognition. The input of the system is generally one or a series of face images with undetermined identities, as well as several face images with known identities in the face database or corresponding codes, and ...

AI Technical Summary

Problems solved by technology

Although this patent document can improve the accuracy of face recognition, it will cause blurred graphics after multiple recognitions, and the requirements for mobile phones are relatively high when using mobile phone recognition, and the recognition rate of some mobile phones is not clear enough.