Abstract
Automatic edge detection is an important and noninvasive step in skin lesion identification. In this paper, the segmentation of skin lesion image is proposed by using edge detection operator with an adjusted threshold value. The clinical skin lesion image is first preprocessed via hair removal, contrast enhancement, and filtering techniques. After this, the skin lesion is segmented using a standard edge detection technique. The fudge factor is introduced and tuned in this detection to adjust the threshold value. For comparative study, Sobel, Prewitt, and Canny edge detection techniques are applied in the skin lesion image. The segmented outputs are compared using entropy and dice similarity index values of the segmented image.
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Sengupta, S., Mittal, N., Modi, M. (2019). Segmentation of Skin Lesion Images Using Fudge Factor Based Techniques. In: Kumar, M., Pandey, R., Kumar, V. (eds) Advances in Interdisciplinary Engineering . Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-6577-5_81
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DOI: https://doi.org/10.1007/978-981-13-6577-5_81
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