Texture Segmentation Using Fractal Features
In this work, we propose the application fractal compression techniques to textured images segmentation, and use the transformation coefficients as features for segmentation. The result is improved by combining fractal dimension feature and the transformation coefficients from the original and its filter versions. Feature vectors are clustered together using K-mean algorithm with features pre-smoothing. The numbers of feature are minimized to reach the compromise result. In the integrated approach, we attempt to improve segmentation of texture images using our method. Background knowledge of image segmentation and image compression will be presented. Algorithms for fractal dimension calculation, K-means clustering, and fractal compression is given. Experimental results are included, and possible future work is mentioned.
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Bachelor of Science (B.S.)
College of Engineering
Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic
Length of Campus-only Access
Honors in the Major Thesis
Pongratananukul, Nattorn, "Texture Segmentation Using Fractal Features" (2000). HIM 1990-2015. 192.