Degraded document image enhancement

Abstract

Poor quality documents are obtained in various situations such as historical document collections, legal archives, security investigations, and documents found in clandestine locations. Such documents are often scanned for automated analysis, further processing, and archiving. Due to the nature of such documents, degraded document images are often hard to read, have low contrast, and are corrupted by various artifacts. We describe a novel approach for the enhancement of such documents based on probabilistic models which increases the contrast, and thus, readability of such documents under various degradations. The enhancement produced by the proposed approach can be viewed under different viewing conditions if desired. The proposed approach was evaluated qualitatively and compared to standard enhancement techniques on a subset of historical documents obtained from the Yad Vashem Holocaust museum. In addition, quantitative performance was evaluated based on synthetically generated data corrupted under various degradation models. Preliminary results demonstrate the effectiveness of the proposed approach.