Study Of The Face Recognition Technology In The Attendance System

Biological characteristics include iris, facial features, palmprint, fingerprint, joint, etc. It is accompanied by the generation of organisms. It is the essential attribute of the organism. It has very strong stability and difference. Along with the progress of science and technology and the need of social development, biometric identification plays an important role in the security system verification, identification of criminal characteristics, credit card verification and so on. A complete biometric identification system should include information acquisition, image processing, data storage, and matching ratio of biological characteristics.As one of the hot spots in the field of biometric recognition, face recognition technology has a very rich theoretical research and results show. Compared with iris and palmprint biometric recognition technology, face recognition technology is easier to be accepted by the majority of social groups, and it is also easier to implement in feature extraction and system development. This paper focuses on the original data collection of human facial features, discussing binary particle swarm algorithm, PCA algorithm, PCNN algorithm. By the comparison of the characteristic and the result, we analyze the application of the three kinds of the data acquisition algorithm and choose one kind of algorithm as the support to realize the whole system development and application. This thesis includes the following aspects:(1) Taking the human facial features as the starting point, we carefully study the human facial features to find that facial organs have all the biological characteristics that are needed to construct a feature recognition system.(2) According to the rules and characteristics of the human facial features, we carefully analyzed binary particle swarm algorithm, PCA algorithm and PCNN algorithm. By studying the definition of data fusion in the identification, we introduce the correlation coefficient and parameters to control the virtual facial features.(3) In view of the actual effect of above three algorithms, we take PCA as the support of the information acquisition system of the face recognition system, constructing the foreground information collection, comparison system and background database system, using the facial recognition technology into the practical application.