Abstract
This article proposes a scheme for automatic text extraction from scene images. The work is composed of two steps. In the first step, we apply a model based color segmentation procedure in the LCH color space. This step produces certain homogenous connected components (CCs) from the image. In the next step, these CCs are examined in order to identify possible text components. A number of features that distinguish between text and non-text components, are defined. Further, during learning, these features are considered independently and approximated using parametric distribution families. Finally, the joint distribution of the features are constructed using a multivariate Gaussian copula. Consequently, we obtain two copula based class distributions for the two classes (text and non-text). Afterwards, during testing, a CC belongs to the class that produces the highest class distribution probability. Our experiments are on the database of ICDAR 2003 Robust Reading Competition. The experimental results are satisfactory.
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References
Wu, V., Manmatha, R., Riseman, E.M.: Textfinder: An automatic system to detect and recognize text in images. IEEE Trans. Pattern Anal. Mach. Intell. 21(11), 1224–1229 (1999)
Jung, K., Kim, I.K., Kurata, T., Kourogi, M., Han, H.J.: Text scanner with text detection technology on image sequences. In: Proc. of Int. Conf. on Pattern Recognition, vol. 3, pp. 473–476 (2002)
Ghoshal, R., Roy, A., Parui, S.K.: Recognition of bangla text from scene images through perspective correction. In: Proc. ICIIP, pp. 385–390 (2011)
Mardia, K.V., Jupp, P.: Directional Statistics. John Wiley and Sons Ltd. (2000)
Bahlmann, C.: Directional features in online handwriting recognition. Pattern Recognition 39, 115–125 (2006)
Roy, A., Parui, S.K., Nandi, D., Roy, U.: Color image segmentation using a semi-wrapped gaussian mixture model. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds.) PReMI 2011. LNCS, vol. 6744, pp. 148–153. Springer, Heidelberg (2011)
Roy, A., Parui, S.K., Paul, A., Roy, U.: A color based image segmentation and its application to text segmentation. In: Proc. of Ind. Conf. on Computer Vision, Graphics & Image Processing, pp. 313–319 (2008)
Nelsen, R.B.: An Introduction to Copulas. Springer (2006)
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Ghoshal, R., Roy, A., Parui, S.K. (2013). A Copula Based Statistical Model for Text Extraction from Scene Images. In: Maji, P., Ghosh, A., Murty, M.N., Ghosh, K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2013. Lecture Notes in Computer Science, vol 8251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45062-4_67
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DOI: https://doi.org/10.1007/978-3-642-45062-4_67
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