Digital Image Processing Techniques in Character Recognition - A Survey

Authors

  • Dr. Marlapalli Krishna  Associate professor, Sir C. R. Reddy College of Engineering, Eluru, West Godavari Dt, Andhra Pradesh, India
  • Gunupusala Satyanarayana  Assistant Professor, Sir C. R. Reddy College of Engineering, Eluru, West Godavari Dt, Andhra Pradesh, India
  • V. Devi Satya Sri  M. Tech Student, Sir C. R. Reddy College of Engineering, Eluru, West Godavari Dt, Andhra Pradesh, India

Keywords:

Image Processing, Digital Image Processing, Thresholding, Morphological Thinning, Hough Transform, Character Recognition, Digital Image Processing

Abstract

The digital image processing (DIP) has been employed in a number of areas, particularly for feature extraction and to obtain patterns of digital images. Recognition of characters is a novel problem, and although, currently there are widely-available digital image processing algorithms and implementations that are able to detect characters from images, selection of an appropriate technique that can straightforwardly acclimatize to diverse types of images, that are very specific or complex is very important. This paper presents a brief overview of digital image processing techniques such as image restoration, image enhancements, and feature extraction, a framework for processing images and aims at presenting an adaptable digital image processing method for recognition of characters in digital images.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-12-31

Issue

Volume 2, Issue 6, November-December-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Marlapalli Krishna, Gunupusala Satyanarayana, V. Devi Satya Sri, " Digital Image Processing Techniques in Character Recognition - A Survey, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.95-101, November-December-2017.