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Fuzzy logic color detection: Blue areas in melanoma dermoscopy images
Mounika Lingala1, R Joe Stanley2, Ryan K Rader3
1Department of Electrical and Computer Engineering, Missouri University of Science and Technology, G20 Emerson Electric Company Hall, 301 West 16th Street, Rolla, MO 65409-0040, United States.
Abstract:
Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9-80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades.
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