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Role of Offline Handwritten Character Recognition System in Various Applications

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Ch. N. Manisha, E. Sreenivasa Reddy, Y.K. Sundara Krishna
10.5120/ijca2016908349

Ch.N. Manisha, Sreenivasa E Reddy and Sundara Y K Krishna. Article: Role of Offline Handwritten Character Recognition System in Various Applications. International Journal of Computer Applications 135(2):30-33, February 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Ch.N. Manisha and E. Sreenivasa Reddy and Y. K. Sundara Krishna},
	title = {Article: Role of Offline Handwritten Character Recognition System in Various Applications},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {135},
	number = {2},
	pages = {30-33},
	month = {February},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Offline handwritten character recognition system recognizes characters from images. Since the past few decades, many researchers have been developing various handwritten recognition systems for various languages. This paper demonstrates the role and significance of an offline handwritten character recognition system in various applications.

References

  1. Optical_character_recognition, https://en.wikipedia.org/wiki/Optical_character_recognition
  2. Alfons Juan, Veronica Romero, Joan Andreu Sanchez, Nicolas Serrano, Alejandro H. Toselli and Enrique Vidal. 2010. Handwritten Text Recognition for Ancient Documents. Workshop on Applications of Pattern Analysis. JMLR: Workshop and Conference Proceedings 11 (2010) 58-65.
  3. Junhua Mao, Houqiang Li, Wengang Zhou, Shuicheng Yan and Qi Tian.2013. Scale Based Region Growing For Scene Text Detection. MM’13, Barcelona, Spain.
  4. Rafeeq Abdul Rahman A. Al-Hashemi and Shoroq Almamon Alsharari. 2013. Instant Arabic Translation System for Signboard Images Based on Printed Character Recognition. International Journal of Machine Learning and Computing, 3(4), 384-388.
  5. Vijayaditya Peddinti and Kishore Prahallad. 2010. Significance of vowel epenthesis in Telugu text-to-speech synthesis. In Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, 5348-5351.
  6. Pooja Yadav and Nidhika Yadav. 2015. Handwriting Recognition System - A Review. nternational Journal of Computer Applications. 114(19). 36-40.
  7. Reetika Verma and Rupinder Kaur. 2014. Review on Offline Handwritten Character Recognition using Feed Forward Neural Network and SURF Feature. International Journal of Advanced Research in Computer and Communication Engineering. 3(5). 6665-6668.
  8. Adam Coates, Blake Carpenter, Carl Case, Sanjeev Satheesh, Bipin Suresh, Tao Wang, David J. Wu, Andrew Y. Ng. 2011. Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning. 2011 International Conference on Document Analysis and Recognition.440-445.
  9. Er.Puneet kaur and Er.Balwinder Singh. 2012. Recognition of Signboard Images of Gurmukhi. Journal of Global Research in Computer Science. 3(6). 20-23.
  10. Anoop Rekha. 2012. Offline Handwritten Gurmukhi Character and Numeral Recognition using Different Feature Sets and Classifiers - A Survey. International Journal of Engineering Research and Applications. 2(3). 187-191.

Keywords

Applications, Offline, Handwritten, Recognition, Characters, Role.