Abstract
This paper presents an efficient method of separating words in handwritten legal amounts on bank cheques based on the spatial gaps between connected components. Currently all typical existing gap measures suffer from poor performance due to the inherent problem of underestimation and overestimation. In order to decrease such burden, a modified version for each of those existing measures is explored. Also, a new method of combining three different types of distance measures based on 4-class clustering is proposed to reduce the errors generated by each measure. In experiments on real bank cheque database, the modified distance measures show about 3% of better separation rate than their original counterparts. In addition, by applying the combining method, further improvement in word separation was achieved.
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© 2004 Springer-Verlag Berlin Heidelberg
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Kim, I.C., Kim, K.M., Suen, C.Y. (2004). Word Separation in Handwritten Legal Amounts on Bank Cheques Based on Spatial Gap Distances. In: Orchard, B., Yang, C., Ali, M. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2004. Lecture Notes in Computer Science(), vol 3029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24677-0_47
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DOI: https://doi.org/10.1007/978-3-540-24677-0_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22007-7
Online ISBN: 978-3-540-24677-0
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