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On the choice of gray levels in the problem of texture segmentation of images based on the luminance dependence matrices
Tymchuk Andrey Igorevich

graduate student, Kuban State Technological University

350080 181, kv.103, Russia, Krasnodarskii Krai oblast', g. Krasnodar, ul. Sormovskaya, 181, kv. 103



The object of research is the method of textural image segmentation based on the construction and use of luminance dependence matrices. The subject of the study is the influence of the number of reference gray levels used for computations on the speed and quality of image segmentation. Particular attention is paid to the process of constructing brightness dependency matrices, as well as texture attributes, which are calculated on their basis. In the article the author conclude that the choice of the size of the brightness dependence matrix (the number of gray levels) is certainly an important aspect in solving the image segmentation problem, since it directly affects the segmentation quality and program speed. The research methodology is based on the analysis of the method of textural image segmentation based on luminance dependence matrices, testing the segmentation algorithm based on this approach for various input parameters and analysis of results. The main conclusion of the study is the conclusion about the selection of the best number of gray levels in solving the segmentation problem in terms of productivity and segmentation quality. This conclusion is made on the basis of analysis of the results of the program, which implements the algorithm of image segmentation. The analysis was carried out with respect to the time spent on constructing the matrices and calculating the texture attributes, and also with respect to the value of each texture feature separately. The novelty of the study is to determine the number of reference levels relative to the speed and quality of segmentation.

Keywords: texture characteristic, textural feature, texture analysis, texture segmentation, segment, texture, image processing, Gray Level Co-occurrence Matrix, gray level, pixel



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This article written in Russian. You can find full text of article in Russian here .

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