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Документ Adaptive algorithms of face detection and effectiveness assessment of their use(Національний технічний університет "Харківський політехнічний інститут", 2018) Dergachov, K.; Krasnov, L.; Cheliadin, O.; Zymovin, A.Subject of researc his the detection and recognition of faces. The purpose of this work is creation of modified algorithms of face detection, which are providing automatic brightness stabilization of the analyzed image regardless of brightness level. A technique is proposed for assessing the effectiveness of their work in comparison with the classical algorithm. We will dwell in more detail on the first part of the problem − face detection and recognition. In the meantime,the most popular method used for searching the face area on an image is the Viola-Jones method, which is popular because of its known high speed and efficiency. It is based on an integral image representation, on the method of constructing classifiers based on adaptive boosting algorithm (AdaBoost) and on the combination classifiers in cascade structure method. The Viola-Jones method is firstly using cascades of wavelets (primitives) - Haar features. All of the above made it possible to build a face detector that works in real-time with a fairly high quality. However, there are a lot of disturbing factors, which are limiting the efficiency of such algorithm work. The major of them are spacial face position ambiguity on the analised image and poor quality of stage lighting. The results of the study. The adaptive algorithms of face detection and recognition on digital images and video sequences in real-time, based on the Viola-Jones method, are suggested. An automatic stabilization of frame brightness is additionally added to the classical structure of such algorithms to compensate an effect of changes in the stage illumination level on quality of face detection. The structure of the algorithms is described and the software developed in Python programming language for a face detection and recognition using OpenCV library resources. Video data is processed in real time. An original method for the efficient estimating of the algorithm based on the criterion of the maximum probability of faces and their main elements (eye, nose, mouth) correct detection is proposed and implemented programmatically. The results of work of classic and suggested algorithms are compared. The examples of work and testing of software are given. The use of the obtained results allows to improve the quality of work and the reliability of the results when recognizing faces in different systems.Документ Web-cameras stereo pairscolor correction method аnd its practical implementation(Національний технічний університет "Харківський політехнічний інститут", 2019) Dergachov, K.; Krasnov, L.; Cheliadin, O.; Plakhotnyi, O.Subject of study. The article proposes new method and tool for color correction of web-cameras in stereo vision systems in order to improve the quality of their work. The goalis a comparative analysis of thequality indicators of well-known color correction methods and the development of a new method and working algorithms for the joint procedure for color correc-tion and rectification of video frames of the left and right cameras. Objectives: the task was to carry out a theoretical analy-sis of the quality indicators of well-known color correction algorithms and methods, to develop new working algorithms, write the program codes of these algorithms in Python using the necessary OpenCV functions. Conduct experimental stud-ies of these algorithms. Evaluate the performance of the stereo system in the laboratory, and test the reliability of the results obtained using statistical analysis methods. Methods used: comparative analysis of known methods and algorithms by sta-tistical modeling, synthesis of new algorithms and evaluation of the effectiveness of their work by conducting laboratory field tests.The results obtained: a comparative analysis of the performance of the known methods of color correction of stereo cameras was carried out, new efficient algorithm was proposed for solving this problem. Findings. Scientific novelty of the results: new algorithm for correcting the color balance of webcams used in stereoscopic vision systems have been created, featuring highcolor correction accuracy and working in real time using the functions of the OpenCV library in the Python software environment.