Comparison single thresholding method for handwritten images segmentation

Thresholding is one of the critical steps in pattern recognition and has a significant effect on the upcoming steps of image application, the important objectives of thresholding are as follows, separating objects from background, decreasing the capacity of data consequently increases speed. Handwritten recognition is one of the important issues, which have various applications in mobile devices. Peak signal noise ratio (PSNR) is one of the methods for measurement the quality of images. Our proposed method applies peak signal noise ratio (PSNR) as one of the indicator to segment the images. We also compare our proposed method with other existing methods and the results are comparable. This algorithm can be optimized to increase the performance. The result indicates that the proposed method works in average handwritten images because the PSNR value of proposed method is better than other methods.