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