Journals Proceedings

Abstract

Ant colony optimization is a technique for optimization that was introduced in the early 1990’s. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommunications, such as routing and load balancing. Diabetic is one the important cost related problems. And also it gives the numerous eye problems for humans like Diabetic retinopathy. In this work a new method have been proposed to segment the eye affected by diabetic retinopathy. Segmentation is one of the important modules of any image processing technique. In this work we have proposed the Ant Colony Optimization (ACO) algorithm to segment the Human eye. The performance of the proposed system has been verified and validated with another standard algorithm. This technique is a Novel technique to segment the Diabetic retinopathy and also the proposed technique shows significant results.