Modified Fractal Signature (MFS): a new approach to document analysis for automatic knowledge acquisition

Yuan Y. Tang*, Hong Ma, Dihua Xi, Xiaogang Mao, Ching Y. Suen

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

26 Citations (Scopus)

Abstract

One of the key technologies related to knowledge and data engineering is the acquisition of knowledge and data in the development and utilization of information system and the strategies to capture new knowledge and data. Actually, millions of documents, including technical reports, government files, newspapers, books, magazines, letters, bank checks, etc., have to be processed every day, and knowledge has to be acquired from them. This paper presents a new approach to document analysis for automatic knowledge acquisition. The traditional approaches have two major disadvantages: (1) They are not effective for processing documents with high geometrical complexity. Specially, the top-down approach can process only the simple documents which have specific format or contain some a priori information. (2) The top-down approach needs to split large components into small ones iteratively, while the bottom-up approach needs to merge small components into large ones iteratively. They are time consuming. This new approach is based on modified fractal signature. It can overcome the above weaknesses.

Original languageEnglish
Pages (from-to)747-762
Number of pages16
JournalIEEE Transactions on Knowledge and Data Engineering
Volume9
Issue number5
DOIs
Publication statusPublished - Sept 1997
Externally publishedYes

Scopus Subject Areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

User-Defined Keywords

  • δ-parallel bodies
  • Automatic knowledge acquisition
  • Blanket method
  • Document analysis
  • Minkowski dimension
  • Modified fractal signature

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