Abstract
This paper presents a robust approach to segmenting text embedded in complex background. Our approach consists of four steps: smart sampling, unsupervised clustering, the Bayesian decision, post-processing. The experimental results show that it works effectively, and is more efficient in removing complex background residues than the popular K-means method.
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© 2007 Springer-Verlag Berlin Heidelberg
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Wang, W., Fu, L., Gao, W. (2007). Text Segmentation in Complex Background Based on Color and Scale Information of Character Strokes. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_44
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DOI: https://doi.org/10.1007/978-3-540-77255-2_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77254-5
Online ISBN: 978-3-540-77255-2
eBook Packages: Computer ScienceComputer Science (R0)