Munish Kumar¹, Manish Jindal², and Rajendra Sharma³

¹Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, India

²Department of Computer Science and Applications, Panjab University Regional Centre, India

³Department of Computer Science and Engineering, Thapar University, India

Abstract: This paper presents a new technique for grading the writers based on their handwriting. This process of grading shall be helpful in organizing handwriting competitions and then deciding the winners on the basis of an automated process. For testing data set, we have collected samples from one hundred different writers. In order to establish the correctness of our approach, we have also considered these characters, taken from one printed Gurmukhi font (Anandpur Sahib) in testing data set. For training data set, we have considered these characters, taken from four printed Gurmukhi fonts, namely, Language Materials Project (LMP) Taran, Maharaja, Granthi and Gurmukhi_Lys. Nearest Neighbour classifier has been used for obtaining a classification score for each writer. Finally, the writers are graded based on their classification score.

Keywords: Gradation; feature extraction; peak extent based features; modified division point based features; NN.