Handwritten Devanagari Characters and Numeral Recognition using Multi-Region Uniform Local Binary Pattern

Abstract

Automated offline handwritten character recognition of Devanagari script is a growing area of research in the field of pattern recognition. A new approach for Devanagari handwritten character / digit recognition has been proposed in this paper. This approach employs Uniform Local Binary Pattern (ULBP) operator as the feature extraction method. This operator has great performance in research areas such as texture classification and object recognition, but it has not been used in Devanagari handwritten character/digit recognition problem. The proposed method extracts both local and global features. The proposed method have two steps, in the first step image is preprocessed to remove noise and to convert it to binary image and then resizing it to a fixed size of 48x48. In the second step, ULBP operator is applied to the image to extract global features then input image is divided into 9 blocks, ULBP operator is applied to each block to extract local features. Finally, global and local features are used to train Support Vector Machine(SVM). The proposed method has been tested on large set of handwritten character and numeral database and empirical results reveals that the proposed method yields very good accuracy (98.77%) . To establish the superiority of the proposed method, it has also been compared with the contemporary algorithms. The comparative analysis shows that the proposed method out performs the existing methods.