גהאד אלצאנע

For highly degraded text documents, common tasks such as binarization and line extraction, remain difficult tasks. Equipped with a reliable information regarding the distribution of character dimensions in the document, one can improve results of these algorithms significantly. We introduce a novel perspective of the image data which maps the evolution of connected components along the change in gray scale threshold. We use these maps to provide a robust algorithm for extracting information about character dimensions in degraded documents, and demonstrate improvement in binarization results using this information. We analyze statistically the characteristics of the evolution maps for text documents, and compare our results with ground truth data.