A Review: Image Segmentation Using Genetic Algorithm
Anubha Kale, Anurag Kumar Jain · 2014
Abstract — Image segmentation is an important and difficult task of image processing and the consequent tasks including object detection, feature extraction, object recognition and categorization depend on the quality of segmentation process. In this paper we suggest Genetic Algorithm to solve the problem of image segmentation. The problem was treated as optimization problems based GA. GAs is used to segment an image by using an optimization function without any threshold values. GAs based image segmentation can provide more accurate results than traditional segmentation methods. The genetic procedure provided a faster convergence to the optimal solution. This is because the sampling strategy allows exploring the solution space by a strategy that is not biased. The preliminary results indicate that GA-based methods perform better than the traditional methods in terms of quality. Also, by developing hybrid algorithms such as GAs and Artificial Neural Networks (ANNs) we can reduce the processing time and increase the visual quality of the final segmentation underscoring the advantages of hybrid algorithms.