Abstract
Global and local adaptive thresholding techniques have been shown effective on particular types of documents. None produces consistently good results on all types of documents. In this paper a novel method, called the multistage-approach, is presented and compared against some existing single-stage algorithms. The multistage approach recursively breaks down an image into sub-regions using quad-tree decomposition and extracts local features from each sub-region until an appropriate thresholding method can be applied to each sub-region. Quantitative analysis using word recall and on 300 degraded historical images obtained from the Library of Congress demonstrate the method is superior to any existing single methods.