Zone based Method to Classify Isolated Malayalam Handwritten Characters using Hu-Invariant Moments and Neural Networks
Paulose Raj and Amitabh Wahi. Article: Zone based Method to Classify Isolated Malayalam Handwritten Characters using Hu-Invariant Moments and Neural Networks. IJCA Proceedings on International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences ICIIIOES(5):10-14, December 2013. Full text available. BibTeX
@article{key:article, author = {Paulose Raj and Amitabh Wahi}, title = {Article: Zone based Method to Classify Isolated Malayalam Handwritten Characters using Hu-Invariant Moments and Neural Networks}, journal = {IJCA Proceedings on International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences}, year = {2013}, volume = {ICIIIOES}, number = {5}, pages = {10-14}, month = {December}, note = {Full text available} }
Abstract
Handwritten Character Recognition of Indian languages have been a demanding task in image processing and pattern recognition. Structural complexity and likeness in the characters also increases the complexity in the classification of characters. In this study, Malayalam, a south-Indian language investigated for recognition of its characters using Hu-invariant moments. Moments applied to the preprocessed image after zoning the image. The image divided horizontally, vertically and diagonally to which moments are applied. Feed-forward backpropagation neural network used for classification of characters with two hidden layers. A better Recognition rate of 93. 7 percentagenoted.
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