Document image binarization using local features and Gaussian mixture modeling
作者:
Highlights:
• Background removal technique based on adaptive median filtering and thresholding
• A Local Co-occurrence Map with local contrast can distinguish between document text and document stains and background.
• Low complexity approach with fast and accurate binarization results
摘要
•Background removal technique based on adaptive median filtering and thresholding•A Local Co-occurrence Map with local contrast can distinguish between document text and document stains and background.•Low complexity approach with fast and accurate binarization results
论文关键词:Binarization,Handwritten documents,Historic documents,Classification,Background estimation
论文评审过程:Received 26 October 2013, Revised 19 January 2015, Accepted 8 April 2015, Available online 29 April 2015, Version of Record 15 May 2015.
论文官网地址:https://doi.org/10.1016/j.imavis.2015.04.003