Puzzle based system for improving Arabic handwriting recognition

Several researches have been done through the last years to improve the recognition rate of Arabic handwritten recognition systems. The use of different post-processing techniques for word selection methods such as voting and contextual information was the choice of many systems. In our previous works, we proposed a technique that uses SVM classifier to recognize Arabic handwritten based on two passes horizontal and vertical. In this work, we add a Puzzle algorithm as a post-processor to improve the recognition rate, especially for ambiguous characters. Our method uses a set of stages (filtering, segmentation, features extraction, classification, and post-treatment) and leads to a better classification rate. The approach is tested on Tunisian database IFN/ENIT for handwritten Arabic. It gives encouraging results and opens other perspectives in the domain of Arabic handwritten recognition.