Recognition of Isolated Handwritten Marathi Vowels using Symmetric Density and Moment Invariant Features

In this paper, combination of zone based symmetric density feature and moment invariant feature is proposed for recognition of isolated handwritten Marathi vowels. Recognition of handwritten Marathi vowels is a challenging task due to their interclass structural similarities. Since a standard database does not exist for handwritten Marathi vowels, as a part of this work database of 2294 handwritten Marathi vowels was developed. Pre-processing techniques are applied to remove noise and there zone based symmetric density features are extracted. In addition to zone based symmetric density feature, moment invariants for each image is extracted. Proposed methodology is tested using fivefold cross validation technique; maximum 92. 98 percent recognition accuracy was noted for fold III using SVM classifier. The recognition