Combined horizontal and vertical projection feature extraction technique for Gurmukhi handwritten character recognition

Author

Mahto, Manoj Kumar ; Bhatia, Karamjit ; Sharma, R.K.

Author_Institution

Dept. of Comput. Sci., Gurukul Kangri Vishwavidyalaya, Haridwar, India

fYear

2015

fDate

19-20 March 2015

Firstpage

59

Lastpage

65

Abstract

Despite the advancements in Optical Character Recognition (OCR) technologies, problem of Indic script character recognition remains challenging. Especially in case of handwritten characters the challenges are even more. In this work, we focus on off-line recognition of handwritten characters of Gurmukhi, an Indic script commonly used in state of Punjab in India. As a part of this work, we collected a Gurmukhi character dataset of 3500 images. This dataset is collected from 10 writers. We propose a combined horizontal and vertical projection feature extraction scheme for recognition of Gurmukhi characters. We have tested our method on the collected dataset and achieved a high character recognition accuracy of 98.06%.

Keywords

feature extraction; handwritten character recognition; natural language processing; optical character recognition; Gurmukhi handwritten character recognition; Indic script character recognition; OCR technologies; horizontal projection feature extraction; optical character recognition; vertical projection feature extraction; Accuracy; Character recognition; Feature extraction; Handwriting recognition; Image segmentation; Kernel; Support vector machines; Character Recognition; Feature Extraction; Horizontal Projection; Off-line Handwritten Gurmukhi Character Recognition; Vertical Projection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in

Conference_Location

Ghaziabad

Type

conf

DOI

10.1109/ICACEA.2015.7164646

Filename

7164646