Fractals everywhere
Fractal image compression: theory and application
Fractal image compression: theory and application
Fractal analysis of tumor in brain MR images
Machine Vision and Applications
Retrieving Faces by the PIFS Fractal Code
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
One Dimensional Fractal Coder for Online Signature Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Toward real time fractal image compression using graphics hardware
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Recognition of two-dimensional shapes based on dependence vectors
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
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From the beginning of fractal discovery they found a great number of applications. One of those applications is fractal recognition. In this paper we present some of the weaknesses of the fractal recognition methods and how to eliminate them using the pseudofractal approach. Moreover we introduce a new recognition method of 2D shapes which uses fractal dependence graph introduced by Domaszewicz and Vaishampayan in 1995. The effectiveness of our approach is shown on two test databases.