Abstract
The object of research is the processes of biometric identification and human authentication based on the image of his face for computer vision systems. One of the most problematic places in biometric identification systems using computer vision is the problem of eliminating ambiguity of «scanning». Such ambiguity arises when designing three-dimensional objects of the real world on flat images. In the course of the research, the results of the analysis of the effects of requirements and factors on the features and characteristics of the object of the biometric face recognition system are used. First of all, it is the variability of visual images, the design of three-dimensional objects, the number and location of light sources, the color and intensity of radiation, shadows or reflections from surrounding objects. The solution to the problem of detecting objects on the image lies in the correct choice of the description of objects, for the detection and recognition of which the system is created. Analysis of the features of classes and the properties of face recognition tasks shows that it is sufficient for a database of authentication systems to store a small set of predefined key characteristics, as much as possible characterize the images. Thus, by configuring the system to reduce the probability of incorrect identification, it is possible to use several images belonging to one person. For such purposes, a video sequence of certain specific head movements and facial muscles of the face is sufficient. A generalized algorithm for automatic face detection and recognition is developed. The presented scheme of the generalized algorithm consists of nine simple steps and takes into account the identification features using photo and video images. The advantage of the algorithm is the simplicity of implementation, it allows already at the design stage of the identification system, to quickly evaluate the system's operability by analyzing the internal interaction of its elements.
Highlights
At present, biometric systems of human identification are widely used
Development of the method of principal components based on neural networks is described in [23, 24]. [25] showed the possibility of using the features formed on the later layers of a specialized neural network for the classification of images by the nearest neighbor method. It automatically solves the problems of access control, it is possible to control the conditions for obtaining images that will be stored in the database, and to achieve their compliance with the conditions in which identification of a person will be carried out
Requirements and factors influencing the performance and characteristics of the object of the biometric face recognition system are defined. It is the variability of visual images, the design of threedimensional objects, the number and location of light sources, the color and intensity of radiation, shadows or reflections from surrounding objects
Summary
Biometric systems of human identification are widely used. Classical identification systems require knowledge of the password, the presence of a key, identification card, or other identifying item, it can forget or lose. Biometric systems are based on unique biological characteristics of a person that are difficult to forge and which uniquely identify a particular person Such characteristics include, for example, fingerprints, palm shape, face geometry, iris pattern and retina image [1]. The regular use of traditional technologies, such as password-based identification, is most common in the West. When it comes to managing money assets, people in India (50 %) and China (48 %) are much more likely to trust computer advice than people, while for Canada and the UK this figure was 18 % and 21 %, respectively [2]. The issue of research, improvement and development of modern methods and technologies for human face recognition is an urgent task
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