||Automatic recognition of poorly degraded handwritten text is challenging due to complex layouts and paper degradations over time. Typically, an old manuscript suffers from degradations such as paper stains, faded ink and ink bleed-through. There is variability in writing style, and the presence of text and symbols written in an unknown language. This hampers the document readability, and renders the task of automatic handwritten text recognition (HTR) to be more difficult. We have made recent advances towards enabling high quality automatic document image binarization using the novel methodology of surrogate document quality metrics (DAS 2018), which will be the subject of this talk. I will also briefly discuss related recent contributions in the field of HTR.