Abstract:

The paper deals with the analytical review of application spheres of machine vision-based systems and image processing methods. As a result of the analysis, promising ways of broad implementation of machine vision in the production, caused by an increase in the volume of output and its quality are outlined. Basic components of machine vision systems are thoroughly analyzed and classified by a number of features, their role and level of influence on the quality of the resulting image is defined. Five basic image processing methods are considered. Peculiarities of each of them and their inherent advantages and disadvantages are identified. The problems of implementing such systems in production and the issues of their interaction with manufacturing equipment and available software for production management are considered. The relevance of broad implementation of machine vision systems in different areas of production, from quality control of products to reading their barcodes, is caused primarily by excluding the subjectivity of estimating the monitored parameters because of the human factor. Based on the analysis of applying machine vision systems in production, their main advantage (such as performance, possibility of continuously-long operation, repeatability of measurement results, etc.) and disadvantages (need for high-quality lighting, calibration, etc.) are identified. The analysis data can serve as a basis for determining the conditions of using machine vision systems in particular production conditions. Author Biographies Елена Николаевна Безвесильная, National Technical University of Ukraine "KPI", 37, Avenue Peremogy, Kyiv, Ukraine, 03056 Honored Worker of Science ofUkraineDoctor of engineering, Professor of the Department of Instrumentation

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