Abstract
A large volume of image data is usually stored in the digital library system in a compressed form. Attempts are now being made to perform image processing tasks using the compressed form of images, which can be accessed directly from digital library. The present chapter is focused on two algorithms. In the first algorithm a fractal based image compression technique using genetic algorithms has been suggested. In particular, the genetic algorithm is used as a search technique to make present algorithm faster than the conventional fractal based image compression techniques. In the second one, a new method for extracting edges from the compressed image information has been described. Fractal code obtained from the first algorithm has been used as the input to the second algorithm. Thus the second one can be looked upon as an operation in the compressed domain. Actually, the process of extracting edges is embedded in the process of fractal reconstruction of the original image from the fractal code. Along with the reconstructed image, an edge image is obtained as a by-product. The scheme is unique of its kind as it is not using any kind of convolution operation based on kernels, which is very common in conventional edge detection schemes.
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Mitra, S.K., Murthy, C.A., Kundu, M.K. (2000). Image Compression and Edge Extraction Using Fractal Technique and Genetic Algorithm. In: Pal, S.K., Ghosh, A., Kundu, M.K. (eds) Soft Computing for Image Processing. Studies in Fuzziness and Soft Computing, vol 42. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1858-1_4
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DOI: https://doi.org/10.1007/978-3-7908-1858-1_4
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