A Modified Adaptive Logical Level Binarization Technique for Historical Document Images

Konstantinos Ntirogiannis, Basilis Gatos, Ioannis Pratikakis
2009 2009 10th International Conference on Document Analysis and Recognition  
In this paper, a new document image binarization technique is presented, as an improved version of the state-of-the-art adaptive logical level technique (ALLT). The original ALLT depends on fixed windows to extract essential features such as the character stroke width. Since characters with several different stroke widths may exist within a region, this can lead to erroneous results. In our approach, we use local adaptive binarization as a guide to our adaptive stroke width detection. The
more » ... on and the contour points of the binarization output are combined to identify locally the stroke width. Additionally, we introduce an adaptive local parameter "β" that enhances the characters and improves the overall performance. In this way, we achieve more accurate binarization results in both handwritten and printed documents with a particular focus on degraded historical documents. Experimental results prove the effectiveness of the proposed technique compared to other state-of-the-art methodologies. 10th International Conference on Document Analysis and Recognition 978-0-7695-3725-2/09 $25.00
doi:10.1109/icdar.2009.225 dblp:conf/icdar/NtirogiannisGP09 fatcat:kcsvht35brdxdasjmcwub7gfae