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THE SYSTEM RECOGNIZES SURFACE DEFECTS OF MARBLE SLABS BASED ON SEGMENTATION METHODS | Sipko | Scientific Journal of Astana IT University

THE SYSTEM RECOGNIZES SURFACE DEFECTS OF MARBLE SLABS BASED ON SEGMENTATION METHODS

E. Sipko, O. Kravchenko, A. Karapetyan, Zh. Plakasova, M. Gladka

Аннотация


A system for recognizing surface defects in marble slabs is proposed. The pattern recognition method based on segmentation methods was further developed. The algorithm of the recognition system. The article describes methods for determining damage from digital images on various hard surfaces. Research in this field is relevant for a wide range of industrial enterprises that specialize in the production of various kinds of materials: parts, marble slabs, building materials, etc. To solve this problem, it is proposed to use the k-means clustering method. It has been experimentally established that Gaussian blurring algorithms, the Hough transform, and the Kenny algorithm are best suited for recognizing defects on the surface of a marble slab. The developed complex method based on the theory of pattern recognition allows you to quickly identify defects and damage on the surfaces of marble slabs. On the basis of the method, a system for understanding defects is implemented in software. The main stages of the system are described in the article. The results of the analysis of the image of the surface of the marble slab on a specific example are presented. The developed complex method based on the theory of pattern recognition allows you to quickly identify defects and damage on the surfaces of marble slabs. On the basis of the method, a system for understanding defects is implemented in software. The main stages of the system are described in the article. The results of the analysis of the image of the surface of the marble slab on a specific example are presented.

Ключевые слова


vision system, segmentation, adaptation, method, recognition, digital image.

Полный текст:

PDF (English)

Литература


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DOI: http://dx.doi.org/10.37943/AITU.2020.1.63643

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(P): 2707-9031
(E): 2707-904X

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