Printed amazigh character recognition by a hybrid approach based on Hidden Markov Models and the Hough transform

We present an automatic system for off-line printed Amazigh handwritten characters recognition, based on an hybrid approach combining hidden Markov models (HMM) and the Hough transform. After preprocessing on the image of the character, the representative chain of the character is build from the Hough transformation. This chain is translated into sequence of observations that is used for the learning phase, by the HMM. Finally, we use the Forword classifier to recognize the character. The experimental results show the robustness of the system.