Texture-based Document Binarization

Image binarization, the conversion of a color image into its monochromatic version, plays a key role in many document processing pipelines. The technical literature presents over a hundred different algorithms for document image binarization yielding different quality results, depending on the intrinsic features of the document image. In addition, their processing times vary significantly, influencing their applicability. The fundamental question here is: Which binarization scheme should one choose, from all the available ones, to provide a reasonable quality-time monochromatic image? A recently published paper shows that the analysis of the texture of the paper background of a scanned document may offer elements to select an appropriate binarization algorithm. This work extends such results by analyzing twelve texture descriptors using three distinct distance measures to evaluate 315 binarization schemes, providing solid evidence that the analysis of the paper texture may guide the selection of a suitable binarization algorithm for a given scanned document image.