• Title/Summary/Keyword: 필기체 문장금액

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Spatial Gap Estimation for Word Separation in Handwritten Legal Amounts on BAnk Check (필기체 수표 금액 문장에서의 단어 분리를 위한 공간적 간격 추정)

  • Kim In-cheol;Kim Kyoung-min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.5
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    • pp.1096-1101
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    • 2005
  • An efficient method of estimating the spatial gaps between the connected components has been prposed to separatethe individual words from a handwritten legal amount on bank check. Owing to the inherent problem of underestimation or overestimation, the previous gap measures have much difficulty in being applied to the legal amounts that usually include the great shape variability by writer's unconstrained writing style and touching or irregular gaps between words by space limitation. In order to alleviate such burden and improve word separation performance, we have developed a modified version of each distance measure. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over $2-3\%$ of the word separation rate than their corresponding original distance measures.

Word Separation in Handwritten Legal Amounts on Bank Check by Measuring Gap Distance Between Connected Components (연결 성분 간 간격 측정에 의한 필기체 수표 금액 문장에서의 단어 추출)

  • Kim, In-Cheol
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.57-62
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    • 2004
  • We have proposed an efficient method of word separation in a handwritten legal amount on bank check based on the spatial gaps between the connected components. The previous gap measures all suffer from the inherent problem of underestimation or overestimation that causes a deterioration in separation performance. In order to alleviate such burden, we have developed a modified version of each distance measure. Also, 4 class clustering based method of integrating three different types of distance measures has been proposed to compensate effectively the errors in each measure, whereby further improvement in performance of word separation is expected. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over 2 - 3% of the word separation rate than their corresponding original distance measures. In addition, the proposed combining method based on 4-class clustering achieved further improvement by effectively reducing the errors common to two of three distance measures as well as the individual errors.