Abstract
This paper presents a simple method for segmenting text image on the basis of color components. It is shown how segmentation can benefit from splitting color signals into chromatic and achromatic components and separately smoothing them by proposed clustering method. We analyze and compare the performance of several color components in terms of segmentation of the text regions from color natural scenes. We also perform a fast 1-dimensional k-means clustering algorithm. Therefore we can perform accurate object segmentation using both H and I components. And then, the effectiveness and reliability of proposed method are demonstrated through various natural scene images. The experimental results have proven that the proposed method is effective.
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References
Chen, D., Bourlard, H., Thiran, J.P.: Text identification in complex background using SVM. In: Proc. of the Int. Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 621–626 (2001)
Ohya, J., Shio, A., Aksmatsu, S.: Recognition characters in scene images. IEEE Transaction on Pattern Analysis and Machine Intelligence 16, 214–220 (1994)
Zhong, Y., Karu, K., Jain, A.K.: Locating text in complex color images. Pattern Recognition 28, 1523–1536 (1995)
Sobottka, K., Bunke, H., Kronenberg, H.: Identification of text on colored book and journal covers. In: Int. Conference on Document Analysis and Recognition, pp. 57–63 (1999)
Wu, V., Manmatha, R., Riseman, E.M.: Textfinder: An automatic system to detect and recognize text in images. IEEE Transaction on Pattern Analysis and Machine Intelligence 20, 1224–1229 (1999)
Jain, K., Yu, B.: Automatic text location in images and video frames. Pattern Recognition 31, 2055–2076 (1998)
Haritaoglu, I.: Scene text extraction and translation for handheld devices. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 408–413. IEEE Computer Society Press, Los Alamitos (2001)
Zhang, J., et al.: A PDA-based sign translator. In: IEEE International Conference on Multimodal Interfaces, pp. 217–222. IEEE Computer Society Press, Los Alamitos (2002)
Watanabe, Y., et al.: Translation camera. In: International Conference on Pattern Recognition (1998)
Li, C., Ding, X., Wu, Y.: Automatic text location in natural scene images. In: Int. Conference on Document Analysis and Recognition, pp. 1069–1073 (2001)
Wang, K., Kangas, J.A.: Character location in scene images from digital camera. Pattern Recognition 36, 2287–2299 (2003)
Lucchese, L., Mitra, S.K.: Color image segmentation: A State-of-the-Art Survey. Proc. of the Indian National Science Academy 67, 207–221 (2001)
Guo, P., Lyu, M.R.: A Study on color space selection for determining image segmentation region number. In: Int. Conference on Artificial Intelligence, pp. 1127–1132 (2000)
Cheng, H.D., et al.: Color image segmentation: Advances and Prospects. Pattern Recognition 34, 2259–2281 (2001)
Gao, J., Yang, J.: An adaptive algorithm for text detection from natural scenes. In: Int. Conference Computer Vision and Pattern Recognition, vol. 2, pp. 84–89 (2001)
Wang, X., Ding, X., Liu, C.: Character extraction and recognition in natural scene image. In: Int. Conference on Document Analysis and Recognition, pp. 1084–1088 (2001)
Wang, H.: Automatic character location and segmentation in color scene images. In: International Conference on Image Analysis and Processing, pp. 2–7 (2001)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley-Interscience (2001)
Zhang, C., Wang, P.: A new method of color image segmentation based on intensity and hue clustering. In: Int. Conference on Pattern Recognition, vol. 3, pp. 3617–3621 (2000)
Bezdek, J.C., Pal, N.R.: Some new indexes of cluster validity. IEEE Transactions on Systems, Man, and Cybernetics-Part B 28, 301–315 (1998)
Ray, S., Turi, R.H.: Determination of number of clusters in K-means clustering and application in colour image segmentation. In: International Conference on Advances in Pattern Recognition and Digital Techniques, pp. 27–29 (1999)
Liu, J., Yang, Y.-H.: Multiresolution color image segmentation. IEEE Tran. on Pattern Analysis and Machine Intelligence 16, 689–700 (1994)
Lucas, S.M., et al.: ICDAR2003 robust reading competitions. In: Int. conference on Document Analysis and Recognition, pp. 682–687 (2003)
Bow, S.-T.: Pattern Recognition and Image Processing. Marcel Dekker, New York (2002)
Sural, S., Qian, G., Pramanik, S.: Segmentation and histogram generation using the hsv color space for image retrieval. In: IEEE Int. Conf. on Image Processing, vol. 2, pp. 589–592. IEEE, Los Alamitos (2002)
Comaniciu, D., Meer, P.: Mean shift: A Robust approach towards feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 1–18 (2001)
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Park, J., Yoon, H., Lee, G. (2007). Automatic Segmentation of Natural Scene Images Based on Chromatic and Achromatic Components. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_44
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DOI: https://doi.org/10.1007/978-3-540-71457-6_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71456-9
Online ISBN: 978-3-540-71457-6
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