Abstract
Image edges are the foundation of image texture and shape figure extraction. In this paper we propose a novel edge detection method based on the self-similarity of fractal compression. We point out that the mean-square-error distance (MSE) of fractal compression can be used to extract edge of fractal image effectively. The self-similarity coefficient between the local range block and the searching domain block is centered at the current pixel being processed, and near-center 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 new algorithm for image edge detection is valid and effective. It also has good anti-noise performance.
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Zhang, L., Xi, L. (2007). A Novel Image Edge Detection Using Fractal Compression. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_20
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DOI: https://doi.org/10.1007/978-3-540-74827-4_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74826-7
Online ISBN: 978-3-540-74827-4
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