A novel approach to image edge enhancement using Artificial Bee Colony optimization algorithm for hybridized smoothening filters

In this modern era, image transmission and processing plays a major role. It would not be possible to retrieve information from satellite and medical images without the help of image processing techniques. Image edge enhancement is the art of examining images for identifying objects and judging their significance. The proposed work uses the concept of artificial bee colony algorithm which proved to be the most powerful unbiased optimization technique for sampling a large solution space. Because of its unbiased stochastic sampling, it was quickly adapted in image processing and thus for image edge enhancement as well. This paper deals with the techniques that help in improvising the quality of the image edges and in solving various complex image processing tasks such as segmentation, feature extraction, classification and image generation. The edge enhancement is done using hybridized smoothening filters by the artificial bee colony optimization algorithm and compared it with the genetic algorithm.