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Knowledge-Based Partial Matching: An Efficient Form Classification Method

  • Yungcheol Byun
  • Joongbae Kim
  • Yeongwoo Choi
  • Gyeonghwan Kim
  • Yillbyung Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2390)

Abstract

An efficient method of classifying form is proposed in this paper. Our method identifies a small number of matching areas by their distinctive images with respect to their layout structure and then form classification is performed by matching only these local regions. The process is summarized as follows. First, the form is partitioned into rectangular regions along the locations of lines of the forms. The disparity in each partitioned region of the comparing form images is measured. The penalty for each partitioned area is computed by using the pre-printed text, filled-in data, and the size of a partitioned area. The disparity and penalty are considered to compute the score to select final matching areas. By using our approach, the redundant matching areas are not processed and a feature vector of good quality can be extracted.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Yungcheol Byun
    • 1
  • Joongbae Kim
    • 1
  • Yeongwoo Choi
    • 2
  • Gyeonghwan Kim
    • 3
  • Yillbyung Lee
    • 4
  1. 1.Dept. of ECElectronics and Telecommunications Research InstituteKorea
  2. 2.Dept. of Computer ScienceSookmyung Women’s UniversityKorea
  3. 3.Dept. of Electronic EngineeringSogang UniversityKorea
  4. 4.Dept. of Computer ScienceYonsei UniversityKorea

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