TY - JOUR

T1 - Computer vision algorithms for dermoscopic images

AU - Котина, Елена Дмитриевна

AU - Николюкина, Мария Алексеевна

AU - Патрушев , Александр Владимирович

PY - 2026/6/30

Y1 - 2026/6/30

N2 - The paper proposes algorithms for processing dermoscopic images: a preprocessing algorithm aimed at detecting noise on the image (hair structures and immersion gel bubbles) and subsequent restoration of color characteristics of the noisy skin areas; and a region of interest extraction algorithm that takes into account the specifics of dermoscopic images (possible low contrast in RGB space, characteristic of some types of skin lesions, preservation of hair fragments after preprocessing). The proposed hair detection method is based on a combination of directional Gabor filters and Laplacian of Gaussian filters. This hybrid approach allows for the detection of both thick dark hair structures and thin light ones, demonstrating robustness to the properties of color, direction, and thickness of the detected objects. To minimize false positives at lesion boundaries, an additional geometric analysis of the mask using an elliptical test is proposed. This stage allows for an automatic decision on the need to apply the inpainting procedure, which helps preserve information about the texture of the skin lesion on weakly noisy images.

AB - The paper proposes algorithms for processing dermoscopic images: a preprocessing algorithm aimed at detecting noise on the image (hair structures and immersion gel bubbles) and subsequent restoration of color characteristics of the noisy skin areas; and a region of interest extraction algorithm that takes into account the specifics of dermoscopic images (possible low contrast in RGB space, characteristic of some types of skin lesions, preservation of hair fragments after preprocessing). The proposed hair detection method is based on a combination of directional Gabor filters and Laplacian of Gaussian filters. This hybrid approach allows for the detection of both thick dark hair structures and thin light ones, demonstrating robustness to the properties of color, direction, and thickness of the detected objects. To minimize false positives at lesion boundaries, an additional geometric analysis of the mask using an elliptical test is proposed. This stage allows for an automatic decision on the need to apply the inpainting procedure, which helps preserve information about the texture of the skin lesion on weakly noisy images.

KW - dermoscopy

KW - image processing

KW - segmentation

KW - hair detection

KW - Dermoscopy

KW - Gabor filters

KW - Laplacian of Gaussian

KW - hair detection

KW - image processing

KW - seg-mentation

UR - https://www.mendeley.com/catalogue/26f50718-8e61-322d-88cd-a7dd26b31264/

U2 - 10.35470/2226-4116-2026-15-1-31-37

DO - 10.35470/2226-4116-2026-15-1-31-37

M3 - Article

VL - 15

SP - 31

EP - 37

JO - Cybernetics and Physics

JF - Cybernetics and Physics

SN - 2223-7038

IS - 1

ER -