Author : Maki kadham, Shayma
journal of kerbala university,
2012, Volume 8, Issue 1, Pages 96-104
In this paper, in first stage Ant Colony Optimization (ACO) is introduced to tackle the image edge detection problem, where the aim is to extract the edge information presented in the image, since it is crucial to understand the image’s content. The second stage .A.H. SH Quintet mask Appling for same images to find edge detection. The proposed approach exploits a number of ants, which move on the image driven by the local variation of the image’s intensity values, to establish a pheromone matrix, which represents the edge information at each pixel location for Mycosis Fungoides Skin image Edge detection is proposed.
The third stage compare between first and second stage for Mycosis Fungoides disease. The Skin image have been identified and the edges of the images used for each and every stages that the database consists of 40 images divided each stage of the Mycosis Fungoides disease Skin image 10 images. For each stage a novel algorithm which combines pixel and region based color segmentation techniques is used. The experimental results confirm the effectiveness of the proposed algorithms