Automatic Enhancement and Binarization of Degraded Document Images

Often documents of historic significance are discovered in a state of disrepair. Such documents are commonly scanned to simultaneously archive and publicize a discovery. Converting the information found within such documents to public knowledge occurs more quickly and cheaply if an automatic method to enhance these degraded documents is used instead of enhancing each document image by hand. We describe a novel automated image enhancement approach that requires no training data. The approach is applicable to images of typewritten text as well as hand written text or a mixture of both. The pair of parameters used by the approach is automatically self-tuned according to the input image. The processing of a set of historic documents stored at Yad Vashem Holocaust Memorial Museum in Israel and selected images from the 2011 DIBCO test collection illustrate the approach.