Method of automatic color rendering settings for machine vision systems

Denis D. Shitov; Elena V. Gorbunova; Aleksandr N. Chertov; Valery V. Korotaev

doi:10.1117/12.2061742

23 September 2014 Method of automatic color rendering settings for machine vision systems

Denis D. Shitov, Elena V. Gorbunova, Aleksandr N. Chertov, Valery V. Korotaev

Proceedings Volume 9217, Applications of Digital Image Processing XXXVII; 92170O (2014) https://doi.org/10.1117/12.2061742
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

Today machine vision systems are widely used to solve various problems of observation and control in science and technology, and industrial applications. Generally a color rendering of such systems is sufficient for visual inspection of the process on the screen. However, there is a problem of color rendering settings for machine vision systems when you need to measure the exact color coordinates of the analyzed object at each point of its surface image in automatic mode. To solve this problem there are a number of methods for setting up and improving color rendering of machine vision systems. As a rule, they all have the following disadvantages: the interdependence of two or more functions of the color rendering settings; and the lack of accounting of control objects lighting conditions and its possible changes. This paper presents results of the development of specialized method for machine vision systems color rendering settings. Using this method you can provide the required accuracy of the color analysis of the observed object. The algorithm for automatic setting of color rendering and software implementing it were developed. An experimental study of the algorithm in a variety of lighting conditions and with a few different machine vision systems were carried out.

Citation Download Citation

Denis D. Shitov, Elena V. Gorbunova, Aleksandr N. Chertov, and Valery V. Korotaev "Method of automatic color rendering settings for machine vision systems", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92170O (23 September 2014); https://doi.org/10.1117/12.2061742

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KEYWORDS

Machine vision

Cameras

Radium

Algorithm development

Barium

Control systems

Gallium

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