Improved skin lesion edge detection method using Ant Colony Optimization.

BACKGROUND

Skin lesion edge detection is a significant step in developing an automatized diagnostic system. The efficient diagnostic system leads to correct identification and detection of skin lesion diseases. In this paper, ant colony optimization (ACO) technique is used to improve the edge contour of skin lesion images.

MATERIAL AND METHOD

Firstly, a three-stage preprocessing methodology involving color space conversion, contrast enhancement, and filtering is applied to improve the skin lesion image quality. The edge map is obtained by applying three types of conventional edge detection methods namely Canny, Sobel, and Prewitt. Thereafter, ACO is applied on these images to produce an improved edge contour.

RESULT

The improvement of the proposed methodology is quantitatively verified by analysis of the entropy of the final image obtained by conventional and proposed techniques.

CONCLUSION

From the result analysis, we can conclude that introduction of ACO has increased the efficiency of the conventional edge detection method in skin lesion images.