A Novel Fractal Approach for Persian/Arabic Identification based on Handwriting Recognition

摘要

Problem statement: In recent years, fractal and multi-fractal analysis have been widely applied in many domains, especially in the field of image processing. In this study we presented a novel method for Persian and Arabic text-dependent writer identification based on fractal and multi-fractal features. Approach: From the images of Persian or Arabic words, we calculated their fractal dimensions by using the "Box-counting" method and then we calculated their multi-fractal dimensions by using the method of Diffusion Limited Aggregates (DLA). Results: To evaluate our method, we used 50 writers of the PERSIANDB database, each writer wrote 288 words (24 words repeated 12 times) with 2/3 of words are used for the learning phase and the rest is used for the identification Conclusion: The results obtained by using k nearest neighbor classifier, demonstrated the effectiveness of our proposed method.