Abstract
Fractal image reconstruction through iterated function systems (IFS) is an interesting and challenging topic of research. Several methods have been described in the literature to tackle this issue. However, existing methods have focused exclusively on binary or gray level images. To the best of authors’ knowledge, no method has addressed the problem of colored fractal images so far. This paper fills this gap by introducing a new approach based on the combination of a swarm intelligence method called bat algorithm and a color-based image clustering through multi-level thresholding. To show the performance of the method, an illustrative example is discussed in detail. The numerical and graphical results show that the method is effective and very promising, as it is able to recover both the geometry and color of the input fractal image and yields good (albeit sub-optimal) solutions to this problem.
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Gálvez, A., Fister, I., Fister, I., Iglesias, A. (2022). Image Reconstruction of Colored Bitmap Fractal Images Through Bat Algorithm and Color-Based Image Clustering. In: Sanjurjo González, H., Pastor López, I., García Bringas, P., Quintián, H., Corchado, E. (eds) 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021). SOCO 2021. Advances in Intelligent Systems and Computing, vol 1401. Springer, Cham. https://doi.org/10.1007/978-3-030-87869-6_21
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