Document image zone classification - a simple high-performance approach

نویسندگان

  • Daniel Keysers
  • Faisal Shafait
  • Thomas M. Breuel
چکیده

We describe a simple, fast, and accurate system for document image zone classification — an important subproblem of document image analysis — that results from a detailed analysis of different features. Using a novel combination of known algorithms, we achieve a very competitive error rate of 1.46% (n = 13811) in comparison to (Wang et al., 2006) who report an error rate of 1.55% (n = 24177) using more complicated techniques. The experiments were performed on zones extracted from the widely used UW-III database, which is representative of images of scanned journal pages and contains ground-truthed real-world data.

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تاریخ انتشار 2007