Fuzzy region-growing segmentation of natural images using local fractal dimension

We present a new method that integrates intensity features and a local fractal-dimension feature into a region growing algorithm for the segmentation of natural images. A fuzzy rule is used to integrate different type of feature into a segmentation algorithm. In the proposed algorithm, intensity features are used to produce an accurate segmentation, while the fractal-dimension feature is used to yield a rough segmentation in a natural image. The effective combination of the different features provides the segmented results similar to the ones by a human visual system.

[1]  B. Mandelbrot.  Fractal Geometry of Nature , 1984 .

[2]  Joseph Naor,et al.  Multiple Resolution Texture Analysis and Classification , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Tohru Ishizaka,et al.  Integration of local fractal dimension and boundary edge in segmenting natural images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[4]  Alex Pentland,et al.  Fractal-Based Description of Natural Scenes , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Manfred Glesner,et al.  Image coding with fuzzy region-growing segmentation , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[6]  James M. Keller,et al.  Texture description and segmentation through fractal geometry , 1989, Comput. Vis. Graph. Image Process..