Fractal image compression: theory and application
Fractal image compression: theory and application
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Use of IFS codes for learning 2D isolated-object classification systems
Computer Vision and Image Understanding
On the Fractal Features in Fingerprint Analysis
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Writer Identification based on the fractal construction of a reference base
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Recognition of Persian handwritten digits using image profiles of multiple orientations
Pattern Recognition Letters
Character Representation and Recognition Using Quadtree-based Fractal Encoding Scheme
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition by fractal transformations
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
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Fractal theory has been used for computer graphics, image compression and different fields of pattern recognition. In this paper, a fractal based method for recognition of both on-line and off-line Farsi/ Arabic handwritten digits is proposed. Our main goal is to verify whether fractal theory is able to capture discriminatory information from digits for pattern recognition task. Digit classification problem (on-line and off-line) deals with patterns which do not have complex structure. So, a general purpose fractal coder, introduced for image compression, is simplified to be utilized for this application. In order to do that, during the coding process, contrast and luminosity information of each point in the input pattern are ignored. Therefore, this approach can deal with on-line data and binary images of handwritten Farsi digits. In fact, our system represents the shape of the input pattern by searching for a set of geometrical relationship between parts of it. Some fractal-based features are directly extracted by the fractal coder. We show that the resulting features have invariant properties which can be used for object recognition.