A Multiscale Morphological Binarization Algorithm

Image binarization is widely used to generate more appropriate images to be used in several image analysis and understanding systems, as well as to facilitate data management and decrease storage space requirements. The main difficulties arise from the fact that images are frequently degraded by noise and non-uniform illumination, for example. This paper presents an efficient morphological-based image binarization technique with scale-space properties that is able to cope with these problems. We evaluate the proposed approach for different classes of images, including text images such as historical and machine-printed documents, obtaining promising results.