Abstract
In this paper, we present a novel technique for detection of concave regions as a structural information of character images. The problem difficulty lies in reporting all concavities irrespective of the viewing direction on the 2D plane. In our approach, we detect concave regions by analyzing the sequence of discrete turns taken to describe the character stroke; hence, it becomes view-invariant. The proposed method has the added advantage of detecting same concave regions of a particular character written by different individuals. We have tested our method on printed and handwritten Bangla and Hindi isolated character images. Initial results demonstrate the efficacy of our approach.
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Bag, S., Bhowmick, P., Harit, G. (2012). Detection of Structural Concavities in Character Images—A Writer-Independent Approach. In: Kundu, M.K., Mitra, S., Mazumdar, D., Pal, S.K. (eds) Perception and Machine Intelligence. PerMIn 2012. Lecture Notes in Computer Science, vol 7143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27387-2_33
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DOI: https://doi.org/10.1007/978-3-642-27387-2_33
Publisher Name: Springer, Berlin, Heidelberg
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