Kinshakov, E.Parfenenko, Yu.2025-03-202025-03-202024Kinshakov E. V. Optimizing skin image segmentation with fourier and graph-based methods / Kinshakov E. V., Parfenenko Yu. V. // Теоретичні та прикладні аспекти побудови програмних систем : працi 15 міжнародної науково-практичної конференції, Київ, 23-24 грудня 2024 р. / [за заг. ред.: М. М. Глибовця, Т. В. Панченка та iн. ; Факультет інформатики Національного університету "Києво-Могилянська академія" та ін.]. - Київ : НаУКМА, 2024. - C. 26-28.https://ekmair.ukma.edu.ua/handle/123456789/34055This paper introduces advanced methods for skin disease image segmentation using the Dermnet dataset, one of the largest resources in dermatology. Traditional approaches like Watershed and thresholding often fail due to the complex textures, color variations, and noise present in skin images. To address these challenges, novel techniques were proposed. First, the Fourier transform reduces high-frequency noise, preparing images for segmentation. Then, min-cut/max-flow graph algorithms minimize energy functions, enabling precise separation of pathological and healthy areas. Additionally, a piecewise smooth approximation improves boundary detection, refining segmentation results. Experiments demonstrated a 15% accuracy improvement over traditional methods. Processing time was also significantly reduced, enhancing the reliability and efficiency of automated diagnostic systems.en-USsegmentationmachine learningimage processingskin diseasesFourier transformgraph algorithmscomputational optimizationpiecewise approximationconference materialsConference materials