Research Article
Text Recognition from Complex Colored Images using Neural Network with Discriminative Feature Extraction
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 180 - Issue 3 |
| Published: Dec 2017 |
| Authors: G. Gayathri Devi, G. Sathyanarayanan, C. P. Sumathi |
10.5120/ijca2017915987
|
G. Gayathri Devi, G. Sathyanarayanan, C. P. Sumathi . Text Recognition from Complex Colored Images using Neural Network with Discriminative Feature Extraction. International Journal of Computer Applications. 180, 3 (Dec 2017), 7-12. DOI=10.5120/ijca2017915987
@article{ 10.5120/ijca2017915987,
author = { G. Gayathri Devi,G. Sathyanarayanan,C. P. Sumathi },
title = { Text Recognition from Complex Colored Images using Neural Network with Discriminative Feature Extraction },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 180 },
number = { 3 },
pages = { 7-12 },
doi = { 10.5120/ijca2017915987 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A G. Gayathri Devi
%A G. Sathyanarayanan
%A C. P. Sumathi
%T Text Recognition from Complex Colored Images using Neural Network with Discriminative Feature Extraction%T
%J International Journal of Computer Applications
%V 180
%N 3
%P 7-12
%R 10.5120/ijca2017915987
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The objective of this paper is to project a new methodology for text recognition from the features of segmented text component of images. Text classification algorithm is the main decision making stage of text recognition system. Artificial neural network approach has been used to train and test the character based on the extracted features. Finally, the identified texts are converted in to readable/editable version of text file.
References
- Bolan Su, Shijian Lu, Shangxuan Tian, Joo-Hwee Lim, Chew-Lim Tan. Character Recognition in Natural Scenes using Convolutional Co-occurrence HOG. Pattern Recognition (ICPR), 2014 22nd International Conference on. IEEE, 2014.
- Lukas Neumann and J. Matas, "On combining multiple segmentations in scene text recognition," in Proc. ICDAR, 2013.
- Gokhan Yildirim, R. Achanta, and S. Ssstrunk, "Text Recognition in Natural Images Using Multiclass Hough Forests," in VISAPP, vol. 1, pp. 737-741, 2013.
- Jacqueline L. Feild and E. G. Learned-Miller, “Improving open-vocabulary scene text recognition,” in IEEE International Conference on. Document Analysis and Recognition, pp. 604–608, 2013.
- Tao. Wang, D. Wu, A. Coates, and A. Ng, "End-to-end text recognition with convolutional neural networks," in International Conference on Pattern Recognition, 2012
- Anand Mishra, K. Alahari, and C. V. Jawahar. Top-down and bottom-up cues for scene text recognition. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition( CVPR), 2012
- Alvaro Gonz´alez, Luis M. Bergasa, J. Javier Yebes, Sebasti´an Bronte, “Text Location in Complex Images ”, 21st International Conference on Pattern Recognition (ICPR 2012) , NOV 11-15, Tsukuba, Japan,2012.
- Coates, B. Carpenter, C. Case, S. Satheesh, B. Suresh, T. Wang, D. J. Wu, and A. Y. Ng. Text detection and character recognition in scene images with unsupervised feature learning. In ICDAR, pages 440-445, 2011.
- Deepak Kumar, M N Anil Prasad,A G Ramakrishnan,"Multi-script robust reading competition in ICDAR 2013" , MOCR ’13, Washington, DC, USA,August 24 2013.
- Anurag Bhardwaj, Chen-Yu Lee Wei Di, Vignesh Jagadeesh, and Robinson Piramuthu, “Region-based Discriminative Feature Pooling for Scene Text Recognition”, The 27th Annual Conference of the Japanese Society for Artificial Intelligence, 2013.
- Alessandro L. Koerich, Alceu de Souza Britto Jr., Luiz E. Soares de Oliveira,”Verification of Unconstrained Handwritten Words at Character Level” ,ICFHR,pp 39-44, 2010.
- G. Sathyanarayanan, G. Gayathri Devi and C. P. Sumathi,, International Journal of Computer Engineering and Applications,"Discriminative Feature Extraction Of Text Components From Complex Colored Images", Volume XI, Issue XI, Nov. 17,ISSN 2321-3469.
Index Terms
Keywords