Articles
| Open Access | APPLICATION OF NUMERICAL AND FUNCTIONAL SERIES IN IMAGE ANALYSIS AND SHAPE RECOGNITION AT ALMALYK MINING AND METALLURGICAL COMPLEX
Zokhidjon Miratoev , Assistant, Department of Mathematics and Natural Sciences, Almalyk Branch of TSTU, UzbekistanAbstract
Numerical and functional series play a pivotal role in modeling chemical processes and advancing image processing within chemical engineering. This study explores their application in the Almalyk Mining and Metallurgical Complex (AMMC) "Smart Mine" strategy, with a focus on shape recognition in binary images. Taylor series are employed to approximate shape boundaries in noisy images, Fourier descriptors model closed contours, and Zernike moments enhance shape classification. Through practical examples, a Python implementation, and a comprehensive literature review, this study demonstrates the effectiveness of these methods in ore classification and quality control.
Keywords
Numerical series, Functional series, Taylor series, Fourier descriptors, Zernike moments, Image analysis, Shape recognition, Almalyk Mining and Metallurgical Complex, Smart Mine, Ore classification, Quality control, Image processing, Chemical engineering, Hough transform, Python implementation
References
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