An Efficient Form Classification Method Using Partial Matching
Identifieur interne : 001B13 ( Main/Merge ); précédent : 001B12; suivant : 001B14An Efficient Form Classification Method Using Partial Matching
Auteurs : Yungcheol Byun [Corée du Sud] ; Sungsoo Yoon [Corée du Sud] ; Yeongwoo Choi [Corée du Sud] ; Gyeonghwan Kim [Corée du Sud] ; Yillbyung Lee [Corée du Sud]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2001.
Abstract
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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DOI: 10.1007/3-540-45656-2_9
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<front><div type="abstract" xml:lang="en">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.</div>
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