Title: Unsupervised measures for parameter selection of binarization algorithms
Authors: Ramirez-Ortegon, Marte A ×
Duéñez-Guzmán, Edgar
Rojas, Raul
Cuevas, Erik #
Issue Date: Mar-2011
Publisher: Pergamon Press
Series Title: Pattern Recognition vol:44 issue:3 pages:491-502
Abstract: In this paper, we propose a mechanism for systematic comparison of the efficacy of unsupervised evaluation methods for parameter selection of binarization algorithms in optical character recognition (OCR). We also analyze these measures statistically and ascertain whether a measure is suitable or not to assess a binarization method. The comparison process is streamlined in several steps. Given an unsupervised measure and a binarization algorithm we: (i) find the best parameter combination for the algorithm in terms of the measure, (ii) use the best binarization of an image on an OCR, and (iii) evaluate the accuracy of the characters detected. We also propose a new unsupervised measure and a statistical test to compare measures based on an intuitive triad of possible results: better, worse or comparable performance. The comparison method and statistical tests can be easily generalized for new measures, binarization algorithms and even other accuracy-driven tasks in image processing. Finally, we perform an extensive comparison of several well known measures, binarization algorithms and OCRs, and use it to show the strengths of the WV measure. (C) 2010 Elsevier Ltd. All rights reserved.
ISSN: 0031-3203
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Non-KU Leuven Association publications
× corresponding author
# (joint) last author

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