The Anatomy of Bangla OCR System for Printed Texts using Back Propagation Neural Network

Authors

  • Shamim Ahmed

  • A.K.M. Najmus Sakib

Keywords:

Optical Character Recognition, Binarization, Skew Angle Detection, Segmentation, Artificial Neural Network

Abstract

This paper is based on Bangla (National Language of Bangladesh) Optical Character Recognition process for printed texts and its steps using Back Propagation Neural Network. Bangla character recognition is very important field of research because Bangla is most popular language in the Indian subcontinent. Pre-processing steps that follows are Image Acquisition, binarization, background removal, noise elimination, skew angle detection and correction, noise removal, line, word and character segmentations. In the post processing steps various features are extracted by applying DCT (Discrete Cosine Transform) from segmented characters. The segmented characters are then fed into a three layer feed forward Back Propagation Neural Network for training. Finally this network is used to recognize printed Bangla scripts.

How to Cite

Shamim Ahmed, & A.K.M. Najmus Sakib. (2012). The Anatomy of Bangla OCR System for Printed Texts using Back Propagation Neural Network. Global Journal of Computer Science and Technology, 12(6), 29–38. Retrieved from https://computerresearch.org/index.php/computer/article/view/476

The Anatomy of Bangla OCR System for Printed Texts using Back Propagation Neural Network

Published

2012-03-15