Image Segmentation Euclidean Distance Metric Pattern Feature Extraction Recognition

Character recognition gray-scale character recognition multistage graph search recognition-based segmentation Training Learning rule Distorted patterns In the proposed methodology, the character segmentation regions are determined by using projection profiles and topographic features extracted from the gray-scale images. Then a nonlinear character segmentation path in each character segmentation region is found by using multi-stage graph search algorithm. Finally, in order to confirm the nonlinear character segmentation paths and recognition results, recognition-based segmentation method is adopted. Through the experiments with various kinds of printed documents, it is convinced that the proposed methodology is very effective for the segmentation and recognition of touched and overlapped characters. This paper is an approach to develop a method to get the optimized results using the easily available resources.Segmentation helps to extract out some common features among distinct handwriting styles of different people