Fractal Image Compression Using Genetic Algorithm with Variants of Crossover

Fractal image compression techniques are developed due to recognition that fractals may describe natural scenes greater than shapes of regular geometry. One of the very efficient fractal methods is based on iterated function system (IFS), and may be developed by Bamsley and Jacquin. New techniques for image compression while using the theory of fractal. The fractal codes are made assuming self likeness property of pictures. Fractal image compression explores the self similarity property of your natural image and utilizes the partitioned iterated function system (PIFS) for you to encode it. This system is of excellent interest both in theory and application. On the other hand, it is time-consuming within the encoding process and such drawback makes it Impractical for real-time applications. The time is primarily spent on the look for the best-match block within a large domain swimming pool. In particular, to generate the fractal rules, Genetic Algorithm are utilized which greatly decreases the look for finding self similarity’s within the given image. With this paper the means of Genetic Algorithm (GA) is tried for Fractal Image Data compression (FIC). With assistance from this evolutionary algorithm effort was created to reduce the seek complexity of coordinating between range prohibit and domain prohibit. Keywords— Fractal Image compression, Genetic Algorithm, self similarity, crossover, mutation.