Evolutionary Approach Based on Active Edges Detection for Images Segmentation

• Published in: Journal of applied computer science & mathematics Vol. 9; no. 19; pp. 43 - 49
• Main Authors: Slatnia Sihem, Kazar Okba, Arab Khaoula
• Format: Journal Article
• Language: English
• Published: Stefan cel Mare University of Suceava 01-03-2015
• Subjects: Active edge; genetic algorithm; greedy algorithm; medical image; segmentation
• EISSN: 2066-3129
• ISSN: 2066-4273

There are many methods for segmentation which vary strongly in their approach to the problem of image segmentation. In this paper, We specified the study in a particular segmentation method of radiological images based on the active edges detection. The optimize solutions was chosen as the genetic algorithm optimization method, and to compare this formalism with other existing methods, we chose a greedy algorithm is criterion for its timeliness. we propose a method of genetic active edge detection in images gray level. In fact, for the convergence of the edge to the object edges, we use the classic and the greedy method. Indeed, the proposed method is based on the active edges optimization using the genetic algorithms process to minimize a sum various energies, in order to evolve a population of snakes to an individual who has the minimum energy.