Research of parameters of face recognition algorithms
In today's world, pattern recognition theory plays an important role. It is practically used in face recognition, the task of which is to automatically locate a face in an image and, if necessary, identify a person by face. The transience of modern life dictates the growing demands for more and more new and improved methods of localizing and recognizing faces. Interest in them is quite significant, in view of their wide practical application in areas such as security systems, security systems in places of mass stay of people, anti-terrorism systems, forensic expertise, verification, mobile devices, etc. Personal identification technology based on the face image does not require physical contact with the device, as is required when using other biometric indicators, and taking into account the rapid development of digital technology is the most preferred for mass use. But it has the main difficulty, which consists in the dependence of the quality of the result of recognition of a person on the face image on the position, angle, lighting conditions, etc. This work is devoted to the development of recommendations on the choice of parameters, in conjunction with the algorithm, which at the output will produce the expected accuracy of the result of work. For the analysis, face recognition algorithms were taken: the method of principal components, active appearance models, the method of flexible comparison on graphs, convolutional neural networks. For each of the algorithms, advantages and disadvantages were identified. The architecture of the selected face recognition algorithm is described. The parameters affecting the accuracy of the results of work. According to the results of the study, the shortcomings of the selected algorithm were identified, and variants of the algorithm modification were proposed in order to increase the percentage of recognition accuracy.