Online handwritten character recognition based on online-offline features using BP neural network

Abstract

Efforts in handwriting recognition are still widely research as current techniques are still inadequate and inefficient. In this paper an online handwriting character recognition system based on online-offline features using the back-propagation neural network algorithm. A novel feature of this system is in the feature extraction technique which has been developed based on temporal and spatial handwriting signals. The goal is to improve the feature extraction analysis for online handwriting recognition. The results of recognition rates based on the UNIPEN and IRONOFF databases show a higher rate of accuracy for writer-independent applications.