Degraded Document Image Enhancement Using Hybrid Thresholding and Mathematical Morphology

The paper presents a hybrid thresholding approach for binarization and enhancement of degraded documents. Historical documents contain information of great cultural and scientific value. But such documents are frequently degraded over time. Digitized degraded documents require specialized processing to remove different kinds of noise and to improve readability. The approach for enhancing degraded documents uses a combination of two thresholding algorithms. First, iterative global thresholding is applied to the smoothed degraded image until the stopping criteria is reached. Then a threshold selection method from gray level histogram is used to binarize the image. The next step is detecting areas where noise still remains and applying iterative thresholding locally. A method to improve the quality of textual information in the document is also done as a post processing stage, thus making the approach efficient and better suited for character recognition applications.