"Analysis of Directional Features - Stroke and Contour for Handwritten Character Recognition"

Machine simulation of human functions like recognition of the text is a challenging task. The off-line handwritten character recognition requires more research to reach the ultimate goal of machine recognition of the text. An attempt is made towards English language by a large number of researchers since six decades. But for Indian languages it is still a dream. We propose a method on offline isolated English character. The method is also applied to Marathi vowels. The image acquired is preprocessed to remove all unwanted details from the image so that the image is suitable for feature extraction. Feature extraction plays an important role in handwritten recognition. The two feature extraction methods based on directional features are considered. The first method uses stroke distribution of a character. The second method uses contour extraction. The two directional features are compared with two different correlation techniques separately to check the suitability of the recognition method. First correlation technique calculates the dissimilarity between reference pattern and test pattern, and the other calculates the similarity between reference pattern and test pattern. The result of the comparison is to classify the character under consideration to a class if hit. If miss, the confusion information is extracted for the analysis.