A factor model for detection and recognition of human face contours and elements

The paper deals with the issues of detection and modeling of human faces and objects on a face taken from the images. The model, algorithm and program are developed for the detection of human facial contours and main elements. The preliminary image processing involves the methods of color modeling and color measurements. Well-known methods, including hidden Markov models, are used for image recognition and processing. The training of the developed model was carried out with neural network methods of machine learning based on a specially created sample, as well as using color segmentation methods. A factor model of a human face is created, which makes it possible to select and recognize efficiently a face and its objects in the image at high speed and with a given accuracy. The experiments have shown that the accuracy of the correct selection of boundaries was about 95–96 % after training. The developed model can be used in security assurance tasks, namely to search and identify criminals, to strengthen law and order, to control access to critical infrastructure facilities, etc.