Abstract
In optical character recognition, text strings are extracted from images so that it can be edited, formatted, indexed, searched, or translated. Characters should be grouped into text strings before recognition, but the existing methods cannot group characters accurately. This paper proposes a new approach to group characters into text strings based on the consistency constraints. According to the features of the characters in the topographic maps, three kinds of consistency constraints are proposed, which are the color, size and direction consistency constraint respectively. In the proposed method, due to the introduction of the color consistency constraint, the characters with different colors can be grouped well; and this method can deal with the curved character strings more accurately by the improved direction consistency constraint. The final experimental results show that this method can group the characters more accurately, and lay a good foundation for text recognition.
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Xu, P., Miao, Q., Liu, R., Chen, F., Chen, X., Nie, W. (2015). A Novel Dynamic Character Grouping Approach Based on the Consistency Constraints. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48570-5_17
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DOI: https://doi.org/10.1007/978-3-662-48570-5_17
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