An Analytical Study of different Document Image Binarization Methods
This work addresses the problem of improving document image processing for text and shape recognition applications, but it is incremental as it builds on established techniques.
The paper studied existing document image binarization methods, comparing their advantages and disadvantages, and modified some algorithms to optimize time or performance, but did not report specific numerical results.
Document image has been the area of research for a couple of decades because of its potential application in the area of text recognition, line recognition or any other shape recognition from the image. For most of these purposes binarization of image becomes mandatory as far as recognition is concerned. Throughout couple decades standard algorithms have already been developed for this purpose. Some of these algorithms are applicable to degraded image also. Our objective behind this work is to study the existing techniques, compare them in view of advantages and disadvantages and modify some of these algorithms to optimize time or performance.