A novel statistical feature extraction method for textual images: Optical font recognition
Expert Systems with Applications: An International Journal
Offline handwritten word recognition in Hindi
Proceeding of the workshop on Document Analysis and Recognition
Unconstrained handwritten Devanagari character recognition using convolutional neural networks
Proceedings of the 4th International Workshop on Multilingual OCR
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In recent years research towards Indian handwritten character recognition is getting increasing attention. Many approaches have been proposed by the researchers towards handwritten Indian character recognition and many recognition systems for isolated handwritten numerals/characters are available in the literature. To get idea of the recognition results of different classifiers and to provide new benchmark for future research, in this paper a comparative study of Devnagari handwritten character recognition using twelve different classifiers and four sets of feature is presented. Projection distance, subspace method, linear discriminant function, support vector machines, modified quadratic discriminant function, mirror image learning, Euclidean distance, nearest neighbour, k-Nearest neighbour, modified projection distance, compound projection distance, and compound modified quadratic discriminant function are used as different classifiers. Feature sets used in the classifiers are computed based on curvature and gradient information obtained from binary as well as gray-scale images.