Berthe Kya and Yang Yang, Optimization of Fractal Iterated Function System(IFS) with Probability and Fractal Image Generation, J. Univ. Sci. Technol. Beijing, 8(2001), No. 2, pp. 152-156.
Cite this article as:
Berthe Kya and Yang Yang, Optimization of Fractal Iterated Function System(IFS) with Probability and Fractal Image Generation, J. Univ. Sci. Technol. Beijing, 8(2001), No. 2, pp. 152-156.
Berthe Kya and Yang Yang, Optimization of Fractal Iterated Function System(IFS) with Probability and Fractal Image Generation, J. Univ. Sci. Technol. Beijing, 8(2001), No. 2, pp. 152-156.
Citation:
Berthe Kya and Yang Yang, Optimization of Fractal Iterated Function System(IFS) with Probability and Fractal Image Generation, J. Univ. Sci. Technol. Beijing, 8(2001), No. 2, pp. 152-156.
Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China
中文摘要
There are several methods for rendering fractal images based on IFS (Iterated Function System) in computer graphic; but one concern of the computer graphic community has been the efficiency rendering algorithms. The invariant measures arising from IFSP (Iterate Function System with Probability) using the probabilistic algorithm are also known as chaos games. The role of these probabilities to generate the image of the attractor has been investigated using a multi-fractal analysis. The conventional choice of probability associated with each set |S| to generate the attractor in least time possible is introduced, then a new method based on the self similarity and multi-fractal analysis is presented. The efficiency of the new method has been proved over the conventional method.
There are several methods for rendering fractal images based on IFS (Iterated Function System) in computer graphic; but one concern of the computer graphic community has been the efficiency rendering algorithms. The invariant measures arising from IFSP (Iterate Function System with Probability) using the probabilistic algorithm are also known as chaos games. The role of these probabilities to generate the image of the attractor has been investigated using a multi-fractal analysis. The conventional choice of probability associated with each set |S| to generate the attractor in least time possible is introduced, then a new method based on the self similarity and multi-fractal analysis is presented. The efficiency of the new method has been proved over the conventional method.
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