A Proposed method for EDGE Detection of and Image Based on Self-Similarity Parameterisation by Fractal Coding

Detecting edges is a basic operation in image processing. The edges of items in an image hold much of the information in the image. Fractal based image coding gives some desirable properties like resolution independence, fast decoding, and very competitive rate-distortion curves. For any image edges are the foundation of image texture and shape figure extraction. In this paper we propose a method for edge detection of an image based on self-similarity of fractal coding parameterisation. From the experimental result we discovered that mean-square-error distance (MSE) can be used to extract edge of fractal image very effectively. The self-similarity coefficient between the local range block and the searching domain block is centered at the current pixel being processed and nearcenter self-affine transform is applied in local searching process, finally a binary operator is used to threshold its magnitude and produce the edge map of the image. The results of experiments show that the proposed method for edge detection is valid and effective.