Slant Correction of Gurmukhi Text Words from Natural Scene Images

Balwinder Singh*, Raman Maini**
* Assistant Professor, Department of Computer Science Engineering, Yadavindra College of Engineering, Punjabi University, Guru Kashi Campus, Talwandi Sabo, India.
** Professor, Department of Computer Engineering, Punjabi University, Patiala, India.
Periodicity:June - August'2017
DOI : https://doi.org/10.26634/jit.6.3.13781

Abstract

Slant correction is generally performed to normalise handwritten characters to improve the results of recognition. But, natural scene images containing printed text suffer from both skew and slant deformation due to 3D tilt and projective transformation. In this study, a slant correction technique for natural scene images containing Gurmukhi text words has been proposed.The skew normalized Gurmukhi words are firstly transformed to salient image and Hough transform is then applied onto edge image obtained through Sobel operator in vertical direction. Of all the lines identified by Hough transform, the angle of longest line with vertical axis is inferred as the slant angle of Gurmukhi word. Horizontal affine shear transformation with previously determined slant angle is carried out to correct slant in word image. Experimental results show that the method is very effective for slant correction of Gurmukhi words from scene images. The method works equally well for other headline based Indian scripts like Devanagari as well without any modification.

Keywords

Gurmukhi, Hough Transform, Natural Scene Images, Slant Correction.

How to Cite this Article?

Singh, B. and Maini, R. (2017). Slant Correction of Gurmukhi Text Words from Natural Scene Images. i-manager’s Journal on Information Technology, 6(3), 25-29. https://doi.org/10.26634/jit.6.3.13781

References

[1]. Abràmoff, M. D., Magalhães, P. J., & Ram, S. J. (2004). Image processing with ImageJ. Biophotonics International, 11(7), 36-42.
[2]. Achanta, R., Hemami, S., Estrada, F., & Susstrunk, S. (2009, June). Frequency-tuned salient region detection. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on (pp. 1597-1604). IEEE.
[3]. Baird, H. S. (1997). The skew angle of printed documents. In Lawrence O'Gorman & Rangachar Kasturi, Ed., Document Image Analysis (ch. 12, pp. 204–208). Los Alamitos, CA: IEEE Computer Society Press.
[4]. Chaudhuri, B. B., & Pal, U. (1997). Skew angle detection of digitized Indian script documents. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(2), 182-186.
[5]. Jagannathan, L., & Jawahar, C. V. (2005, August). Perspective correction methods for camera based document analysis. In Proc. First Int. Workshop on Camera-based Document Analysis and Recognition (pp. 148-154).
[6]. Kaur, A., Dhir, R., & Lehal, G. S. (2017). A survey on camera-captured scene text detection and extraction: towards Gurmukhi script. International Journal of Multimedia Information Retrieval, 6(2), 115-142.
[7]. Lehal, G. S. (2009). A Complete Machine-Printed Gurmukhi OCR System. In Guide to OCR for Indic Scripts (pp. 43-71). Springer London.
[8]. Lehal, G. S., & Dhir, R. (1999, September). A range free skew detection technique for digitized Gurmukhi script documents. In Document Analysis and Recognition, 1999. ICDAR'99. Proceedings of the Fifth International Conference on (pp. 147-152). IEEE.
[9]. Murthy, O. R., Roy, S., Narang, V., Hanmandlu, M., & Gupta, S. (2013). An approach to divide pre-detected Devanagari words from the scene images into characters. Signal, Image and Video Processing, 7(6), 1071-1082.
[10]. Sharma, D. V., & Lehal, G. S. (2009, July). A fast skew detection and correction algorithm for machine printed words in Gurmukhi script. In Proceedings of the International Workshop on Multilingual OCR (p. 15). ACM.
[11]. Singh, B., & Maini, R. (2016). Skew Detection and Correction of Gurmukhi Words from Natural Scene Images. International Journal of Signal Processing, Image Processing and Pattern Recognition, 9(9), 139- 146.
[12]. Singh, C., Bhatia, N., & Kaur, A. (2008). Hough transform based fast skew detection and accurate skew correction methods. Pattern Recognition, 41(12), 3528- 3546.
[13]. Sun, C., & Si, D. (1997, August). Skew and slant correction for document images using gradient direction. In Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on (Vol. 1, pp. 142-146). IEEE.
[14]. Uchida, S. (2014). Text localization and recognition in images and video. In Handbook of Document Image Processing and Recognition (pp. 843-883). Springer London.
[15]. Yamaguchi, T., Maruyama, M., Miyao, H., & Nakano, Y. (2005). Digit recognition in a natural scene with skew and slant normalization. International Journal on Document Analysis and Recognition, 7(2), 168-177.
[16]. Zhang, X., Lin, Z., Sun, F., & Ma, Y. (2014). Transform invariant text extraction. The Visual Computer, 30(4), 401- 415.
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