ALGORITHMS FOR DEFECT RECOGNITION IN TWO-COMPONENT COMPOSITE COATINGS BASED ON THEIR IMAGES 

Victoria V. Kiyashchenko, Postgraduate student, junior researcher of the laboratory of digital doubles of materials and technological processes of their processing, Samara State Technical University (244 Molodogvardeyskaya street, Samara, Russia), E-mail: vv.kiyashchenko@gmail.com 

Background. This study addresses the issue of automated defect recognition in two-component composite coatings. The research aims to develop an efficient informationmeasuring system that utilizes modern technologies for detecting and characterizing defects on material surfaces. The research goal is to ensure high-precision and automated quality control of coatings, which is crucial in fields where even minor defects can lead to serious consequences. Materials and methods. To achieve the set objectives, the Java programming language and the OpenCV library for image processing are employed. The system analyzes the structure of coatings, including the separation of the boundary of contact between two components, calculation of the specific area of contact, detection of defects in the distribution of materials. Additionally, the Tesseract library is utilized for determining image scale. Results. The developed system successfully identifies defects in two-component composite coatings, providing precise measurements and characteristics of surface defects. Conclusions. The research results confirm the effectiveness of the developed system in defect recognition in two-component composite coatings. Implementing this system into industrial processes for material quality control promises to enhance efficiency and accuracy. 

defect recognition, two-component composite coatings, information-measuring system, image processing, material quality control 

Kiyashchenko V.V. Algorithms for defect recognition in two-component composite coatings based on their images. Modeli, sistemy, seti v ekonomike, tekhnike, prirode i obshchestve = Models, systems, networks in economics, technology, nature and society. 2024;(1):126–138. (In Russ.). doi: 10.21685/2227-8486-2024-1-9