A General Approach to Quality Evaluation of Document Segmentation Results

  • Michael Thulke
  • Volker Märgner
  • Andreas Denge
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1655)

Abstract

In order to increase the performance of document analysis systems a detailed quality evaluation of the achieved results is required. By focussing on segmentation algorithms, we point out that the results produced by the module under consideration should be evaluated directly; we will show that the text-based evaluation method which is often used in the document analysis domain does not accomplish the purpose of a detailed quality evaluation. Therefore, we propose a general evaluation approach for the comparison of segmentation results which is based on the segments directly. This approach is able to handle both algorithms that produce complete segmentations (partition) and algorithms that only extract objects of interest (extraction). Classes of errors are defined in a systematic way, and frequencies for each class can be computed. The evaluation approach is applicable to segmentation or extraction algorithms in a wide range. We have chosen the character segmentation task as an example in order to demonstrate the applicability of our evaluation approach, and we suggest to apply our approach to other segmentation tasks.

Keywords

Ground Truth Segmentation Algorithm Segmentation Result Document Image Text Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Michael Thulke
    • 1
  • Volker Märgner
    • 1
  • Andreas Denge
    • 2
  1. 1.Institute for Communications TechnologyBraunschweig Technical UniversityBraunschweigGermany
  2. 2.German Research Center for Artificial Intelligence (DFKI)KaiserslauternGermany

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