title: A hybrid recognition system for off-line handwritten characters.
abstract: Computer based pattern recognition is a process that involves several sub-processes, including pre-processing, feature extraction, feature selection, and classification. Feature extraction is the estimation of certain attributes of the target patterns. Selection of the right set of features is the most crucial and complex part of building a pattern recognition system. In this work we have combined multiple features extracted using seven different approaches. The novelty of this approach is to achieve better accuracy and reduced computational time for recognition of handwritten characters using Genetic Algorithm which optimizes the number of features along with a simple and adaptive Multi Layer Perceptron classifier. Experiments have been performed using standard database of CEDAR (Centre of Excellence for Document Analysis and Recognition) for English alphabet. The experimental results obtained on this database demonstrate the effectiveness of this system.
authors.affiliation: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India ; ITS Engineering College, 46 Knowledge Park, Greater Noida, Uttar Pradesh 201308 India.
authors.forename: Gauri
authors.initials: G
authors.lastname: Katiyar
authors.affiliation: Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India.
authors.forename: Shabana
authors.initials: S
authors.lastname: Mehfuz
keywords: Character recognition; Feature extraction; Genetic Algorithm; Multi layer perceptron