Abstract
In this paper, we are proposing an efficient method of classifying form that is applicable in real life. Our method will identify a small number of local regions by their distinctive images with respect to their layout structure and then by using the DP (Dynamic Programming) matching to match only these local regions. The disparity score in each local region is defined and measured to select the matching regions. Genetic Algorithm will also be applied to select the best regions of matching from the viewpoint of a performance. Our approach of searching and matching only a small number of structurally distinctive local regions would reduce the processing time and yield a high rate of classification.
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© 2001 Springer-Verlag Berlin Heidelberg
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Byun, Y., Yoon, S., Choi, Y., Kim, G., Lee, Y. (2001). An Efficient Form Classification Method Using Partial Matching. In: Stumptner, M., Corbett, D., Brooks, M. (eds) AI 2001: Advances in Artificial Intelligence. AI 2001. Lecture Notes in Computer Science(), vol 2256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45656-2_9
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DOI: https://doi.org/10.1007/3-540-45656-2_9
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42960-9
Online ISBN: 978-3-540-45656-8
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