Document Type
Conference Proceeding
Publication Date
2019
Abstract
The ICDAR 2019 Time-Quality Binarization Competition assessed the performance of seventeen new together with thirty previously published binarization algorithms. The quality of the resulting two-tone image and the execution time were assessed. Comparisons were on both in "real-world" and synthetic scanned images, and in documents photographed with four models of widely used portable phones. Most of the submitted algorithms employed machine learning techniques and performed best on the most complex images. Traditional algorithms provided very good results at a fraction of the time.
Copyright Statement
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Doi: https://doi.org/10.1109/ICDAR.2019.00248
Publication Information
Dueire Lins, Rafael; Kavallieratou, Ergina; Barney Smith, Elisa; Barros Bernardino, Rodrigo; and Marinho de Jesus, Darlisson. (2019). "ICDAR 2019 Time-Quality Binarization Competition". In 2019 International Conference on Document Analysis and Recognition (ICDAR) (pp. 1539-1546). IEEE. https://doi.org/10.1109/ICDAR.2019.00248