Improvement of Computer Recognition of Foam Layer Criteria
A.V. ZatonskiyPerm National Research Polytechnic University,Automation of Technological Processes,Perm,RussiaRuslan BazhenovSholom-Aleichem Priamursky State University,Information Systems and Mathematics,Birobidzhan,RussiaA. K. OrozobekovaKyrgyz State University of Construction, Transport and Architecture name of N.Isanov,Applied Computer Science,Bishkek,Kyrgyz RepublicSaida BeknazarovaTashkent University of Information Technologies named by Muhammad Al-Khwarizmi,Audiovisual Technologies,Tashkent,UzbekistanTatiana GorbunovaMoscow State University of Civil Engineering,Applied Mathematics,Moscow,RussiaIrina A. LedovskikhPacific National University,Mathematics and Information Technology,Khabarovsk,Russia
2022 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS)conference2022en
ABI
Annotatsiya
Foam bed flotation processes are common in the poly metallic, potash and food industries. A worker who visually assesses the condition of the foam bed controls the process. This reduces process control and product quality because of the human factor. Using computer vision is based on bubble boundary recognition to control due to poor lighting, low foam contrast, and splash back. Recognition is possible by analyzing the glare from the foam surface. We attempt to improve recognition by accounting for the dark antiglare that takes place due to the bubble deformation. It improved recognition and reduced the noise of the method to a few percents.
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