Abstract
In this paper, we introduce a system that aims at recognizing chart images using a model-based approach. First of all, basic chart models are designed for four different chart types based on their characteristics. In a chart model, basic object features and constraints between objects are defined. During the chart recognition, there are two levels of matching: feature level matching to locate basic objects and object level matching to fit in an existing chart model. After the type of a chart is determined, the next step is to do data interpretation and recover the electronic form of the chart image by examining the object attributes. Experiments were done using a set of testing images downloaded from the internet or scanned from books and papers. The results of type determination and the accuracies of the recovered data are reported.
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References
Zhou, Y.P., Tan, C.L.: Hough technique for bar charts detection and recognition in document images. In: International Conference on Image Processing, pp. 494–497 (2000)
Zhou, Y.P., Tan, C.L.: Learning-based scientific chart recognition. In: 4th IAPR International Workshop on Graphics Recognition, GREC 2001, pp. 482–492 (2001)
Song, J., Su, F., Chen, J., Tai, C.L., Cai, S.: Line net global vectorization: an algorithm and its performance analysis. In: IEEE Conference on Computer Vision and Pattern Recognition, South Carolina, pp. 383–388 (2000)
Tombre, K., Tabbone, S., Pélissier, L., Lamiroy, B., Dosch, P.: Text/Graphics Separation Revisited. In: Lopresti, D.P., Hu, J., Kashi, R.S. (eds.) DAS 2002. LNCS, vol. 2423, pp. 200–211. Springer, Heidelberg (2002)
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Huang, W., Tan, C.L., Leow, W.K. (2004). Model-Based Chart Image Recognition. In: Lladós, J., Kwon, YB. (eds) Graphics Recognition. Recent Advances and Perspectives. GREC 2003. Lecture Notes in Computer Science, vol 3088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25977-0_8
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DOI: https://doi.org/10.1007/978-3-540-25977-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22478-5
Online ISBN: 978-3-540-25977-0
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