The week's pick
Random Articles
Reseach Article
A Novel Stroke Width Based Binarization Method to Handle Closely Spaced Thick Characters
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 23 |
| Year of Publication: 2010 |
| Authors: P. Pavan Kumar, Atul Negi, B.L. Deekshatulu, Chakravarthy Bhagvati, Arun Agarwal |
10.5120/540-704
|
P. Pavan Kumar, Atul Negi, B.L. Deekshatulu, Chakravarthy Bhagvati, Arun Agarwal . A Novel Stroke Width Based Binarization Method to Handle Closely Spaced Thick Characters. International Journal of Computer Applications. 1, 23 ( February 2010), 32-39. DOI=10.5120/540-704
Abstract
Signboards and billboards provide a challenge to image seg¬mentation methods, since these images may also have pictures and graphical objects, apart from text objects. Methods that often succeed in more traditional text block segmentation situations do not perform well here since estimation of text lines and character widths etc fail due to the short sample sizes. Further, extraction of characters of different font sizes, which can be found in the real world and signboard images, remains a problem. In this paper, as a solution to the mentioned problem, we propose two stroke width based binarization approaches. These approaches can be used to eliminate extraneous objects based upon estimates of stroke width. We compare our methods with several other stroke width based binarization methods. We observe that the previous approaches fail, when there are closely spaced thick characters. We show that our second approach is able to extract closely spaced thick characters better than any of the other methods.
References
- N. Otsu, ”A threshold selection method from grey level histograms”, IEEE Trans. Syst., Man,Cybern., SMC-8, pp. 62-66, 1978.
- M. Cheriet and J.N. Said and C.Y. Suen, ”A recursive thresholding technique for image segmentation”, IEEE Trans. Image Processing, vol. 7, pp.918-921, June 1998.
- W. Niblack, An Introduction to Digital Image Processing, Prentice Hall, 1986.
- J. Bernsen, ”Dynamic thresholding of gray level images”, Proc. 8th Int. Conf. on Pattern Recognition, vol. 2, pp. 1251-1255, 1986.
- Q.D. Trier and A. K. Jain, ”Goal-directed evaluation of binarization methods”, IEEE Trans. Pattern Anal.Machine Intell., vol. 17, pp. 1191-1201, 1995.
- Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Pearson Education Indian Reprint, 2nd edition, 2003.
- Pietro Perona and Jitendra Malik, ”Scale space and edge detection using anisotropic diffusion”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 7, pp. 629-639, July 1990.
- Liying Fan, Chew Lim Tan, Lixin Fan, ”Edge preserving prefiltering for document image binarization”, Proc. ICIP 01,IEEE Computer Society Press, pp. 1070-1073, 2001.
- M. Kamel and A. Zhao, ”Extraction of binary character/graphics images from gray scale document images”, CVGIP:Graph Models Image Process., vol. 55, no. 3, pp. 203-217, 1993.
- S. Djeziri, F. Nouboud, R. Plamondon, ”Extraction of signatures from check background based on filiformity criterion”, IEEE Transactions on Image Processing, vol. 7, pp. 1425-1438, October 1998.
- Xiangyun Ye, Mohamed Cheriet, Ching Y. Suen, ”Stroke-Model-Based Character Extraction from Gray-Level Document Images”, IEEE Transactions on Image Processing, vol. 10, no. 8, August 2001.
- I.-S. Oh, ”Document image binarization preserving stroke connectivity”, Pattern Recognition Letters, vol. 16, pp. 743-748, 1995.
- P. K. Sahoo, S. Soltani, and A. K. C. Wong, ”SURVEY: A survey of thresholding techniques”, Comput. Vis. Graph. Image Process., vol. 41, pp. 233-260, 1988.
- N. R. Pal and S. Pal, ”A review on image segmentation techniques”, Pattern Recognit., vol. 26, pp. 1277-1294, 1993.
- Second International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2007) September 22, 2007 Grand Hotel Rayon, Curitiba, Brazil. ”http://www.m.cs.osakafu- u.ac.jp/cbdar2007/demo.shtml”.
Index Terms
Keywords