Hybrid algorithms of the person identification by face image

Abstract

In this paper, the problem of constructing hybrid algorithms for identifying a person (IAP) by the image is considered, which is the main one in the development of biometric systems based on them. To solve this problem, we propose a model of algorithms, consisting of the following stages: selection of the area of the face in the image; searching pupils on the face image (FI); determining the location of the mouth and nose; forming a set of geometric features; allocation of subsets of strongly coupled features; the definition of representative features in each subset of strongly related features; interim assessment for the FI class for each set of representative features; estimate for the FI class for all intermediate estimates. A distinctive feature of the proposed hybrid algorithm (HA) is the integration of the results of various methods for determining anthropometric points at the level of calculating the final score for each class of facial images. The main purpose of this paper is to develop an algorithm for integrating various methods of identifying features when IAP on a FI.

Automation of the Agricultural Sector of the Republic of Uzbekistan

“…At that, a particular attention is paid to the modeling of various subsystems in the automation of the agricultural sector. These problems are well studied in various branches of science and technology: in modeling in geomechanics [11][12][13], in solving problems of pattern recognition [14][15][16][17][18] and classification [19,20], medicine [21], in tracking objects based on a Kalman filter [22], modeling of personal identification processes [23], creating a model of an access control system [24], creating models to improve image contrast [25], when modeling predictive indicators [26] and in sports research [27], as well as in hydromechanics [29,29]. In our case, for modeling and automatic control of the agricultural sector, the PHP programming language and the MySQL database, as well as various methods of data mining [30,31], were used.…”