Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers

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 compu...

• Type: Journal
• Year: 2009
• Where: ICDAR
• Authors: Umapada Pal, Tetsushi Wakabayashi, Fumitaka Kimura
• Keywords: Character Recognition, Document Analysis, ICDAR 2009, Projection Distance, Quadratic Discriminant Function