A Novel Handwriting Grading System Using
Gurmukhi
Characters
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.