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Proficient Character Recognition from Images

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Poornima T. M., M. Amanullah

Poornima T M. and M Amanullah. Proficient Character Recognition from Images. International Journal of Computer Applications 143(4):4-7, June 2016. BibTeX

	author = {Poornima T. M. and M. Amanullah},
	title = {Proficient Character Recognition from Images},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {143},
	number = {4},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {4-7},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2016909980},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Reading text from photographs is a challenging problem that has received a significant amount of attention. Two key components of most systems are (i) text detection from images and (ii) text recognition, and many methods have been introduced to design better feature representations and models for both. Scene text recognition has gained significant attention from the computer vision community in recent years. Recognizing text is a difficult problem, even more so than the detection of scanned documents. To evaluate the performance of recent algorithms in detecting and recognizing text from complex images, In this proposed paper implement two method text detection and text recognition . The features extractors are Harris-Corner, Maximal Stable Extremal Regions (MSER), and dense sampling and Histogram of Oriented Gradients (HOG) descriptors. Then implement text recognition. The first one is training a character recognizer to predict the category of a character in an image patch. The second one is training a binary character classifier for each character class to predict the existence of this category in an image patch. The two schemes are compatible with two promising applications related to scene text, which are text understanding and text retrieval. Further we extend this concept with word level recognition with lexicon techniques with accurate results. And also recognition text in real time images, videos and mobile application images.


  1. X. Bai, L. J. Latecki, and W.-Y. Liu, “Skeleton pruning by contour partitioning with discrete curve evolution,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 3, pp. 449–462, Mar. 2007.
  2. R. Beaufort and C. Mancas-Thillou, “A weighted finite-state framework for correcting errors in natural scene OCR,” in Proc. 9th Int. Conf. Document Anal. Recognit., Sep. 2007, pp. 889–893.
  3. X. Chen, J. Yang, J. Zhang, and A. Waibel, “Automatic detection and recognition of signs from natural scenes,” IEEE Trans. Image Process., vol. 13, no. 1, pp. 87–99, Jan. 2004.
  4. A. Coates et al., “Text detection and character recognition in scene images with unsupervised feature learning,” in Proc. ICDAR, Sep. 2011, pp. 440–445.
  5. N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2005, pp. 886–893.
  6. T. de Campos, B. Babu, and M. Varma, “Character recognition in natural images,” in Proc. VISAPP, 2009.
  7. B. Epshtein, E. Ofek, and Y. Wexler, “Detecting text in natural scenes with stroke width transform,” in Proc. CVPR, Jun. 2010, pp. 2963–2970.
  8. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan, “Object detection with discriminatively trained part-based models,”IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 9, pp. 1627–1645, Sep. 2010.
  9. T. Jiang, F. Jurie, and C. Schmid, “Learning shape prior models for object matching,” in Proc. CVPR, Jun. 2009, pp. 848–855.
  10. S. Kumar, R. Gupta, N. Khanna, S. Chaudhury, and S. D. Johsi, “Text extraction and document image segmentation using matched wavelets and MRF model,” IEEE Trans. Image Process., vol. 16, no. 8, pp. 2117–2128, Aug. 2007.


Character Recognition, Text Detection, Text Recognition