Performance Evaluation of Image Binarization Technique for Recognition of Ancient Historical Documents

Information acquisition from degraded historical document has always been a challenging task due to various forms of degradation. Image binarization is very much essential in the restoration of degraded historical documents. Eventhough many algorithms have been proposed, still there is a need for an effective algorithm to solve all kind of degradation problems. In this paper ,an optimum binarization technique is proposed that addresses these issues by using a combined approach of local image contrast and gradient . Firstly,the input image is binarized and then canny egde map is applied to extract text stroke edge pixels.To enhance further,morphological operations are carried out based on shapes.Finally an adaptive thresholding is applied to segment foreground and background pixels.To determine the quality, the proposed method has been tested on 3 public data sets (DIBCO 2009, 2010, 2011) that were taken from pattern recognition and image analysis(PRImA) research lab. Simulation result shows that the proposed binarization method achieves performance improvement interms of F-measure, NRM, MPM, PSNR as 88.4461, 0.0708, 0.00265 and 18.420 respectively.