Earticle

초록

영어

This paper presents a method to use View based approach in Bangla Optical Character Recognition (OCR) system providing reduced data set to the ANN classification engine rather than the traditional OCR methods. It describes how Bangla characters are processed, trained and then recognized with the use of a Backpropagation Artificial neural network. This is the first published account of using a segmentation-free optical character recognition system for Bangla using a view based approach. The methodology presented here assumes that the OCR pre-processor has presented the input images to the classification engine described here. The size and the font face used to render the characters are also significant in both training and classification. The images are first converted into greyscale and then to binary images; these images are then scaled to a fit a pre-determined area with a fixed but significant number of pixels. The feature vectors are then formed extracting the characteristics points, which in this case is simply a series of 0s and 1s of fixed length. Finally, a Artificial neural network is chosen for the training and classification process. Although the steps are simple, and the simplest network is chosen for the training and recognition process.

목차

Abstract
 1. Introduction
  1.1. Optical Character Recognition
  1.2. Overview of Bangla scripts for OCR
 2. Previous work
 3. Properties of Different Bangla Scripts
 4. Our work
  4.1. Pre-processing
  4.2. Data Collection
  4.3. Design Methodology
 5. Result and discussion
  5.1. Bangla Basic Character Recognition Implementation
 6. Future Scope
 7. Conclusion
 References

저자

• Sumana Barman [ Heritage Institute of Technology ]
• Amit Kumar Samant [ IBM India Pvt. Ltd ]
• Tai-hoon Kim [ Hannam University ]
• Debnath Bhattacharyya [ Hannam University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605