A binarization method with learning-built rules for document images produced by cameras

DOI10.1016/j.patcog.2009.10.016zbMath1191.68777OpenAlexW1995971685MaRDI QIDQ962725

Fu Chang, Wen-Hsiung Lin, Chien-Hsing Chou

Publication date: 7 April 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2009.10.016

zbMATH Keywords

image processingsupport vector machineglobal thresholddocument image binarizationlocal thresholdmulti-label problemnon-uniform brightness

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10)

Related Items

Effective document image binarization via a convex variational level set model ⋮ Unsupervised measures for parameter selection of binarization algorithms ⋮ Nonlinear edge-preserving diffusion with adaptive source for document images binarization ⋮ Transition thresholds and transition operators for binarization and edge detection

Uses Software

• BoosTexter

Cites Work

• Unnamed Item
• BoosTexter: A boosting-based system for text categorization
• Support-vector networks
• Stroke-model-based character extraction from gray-level document images
• An algorithm for information structuring and retrieval