Research on Hair Removal Algorithm of Dermatoscopic Images Using Maximum Variance Fuzzy Clustering and Optimized Criminisi Algorithm
July 2022
in “
Biomedical Signal Processing and Control
”
Studysummary This study presents a new hair removal algorithm for dermatoscopic images of skin lesions that improves hair detection accuracy by 2–7% and hair repair accuracy by 2–5% on average, using advanced techniques like maximum variance fuzzy clustering, Criminisi priorities, and the ant colony algorithm.
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