Global word shape processing using polar-radii graphs for offline handwriting recognition

The result of investigating the capability of the polar-radii graph (PRG) of the word contour as a global feature for offline handwriting recognition is presented in this paper. The PRG is combined with the local geometric features to improve the accuracy of the handwriting recognition system. The handwriting recognition system using local features and an HMM recognizer obtained a recognition rate of 58% for a 20-word vocabulary using the demo version of the publicly available IAM database. Using the PRG of the word contour as a global feature and an MLP classifier, the recognition rate is 78%. Using the linear confidence accumulation (LCA) method to combine the results of the recognizers based on the local and global features, an over-all recognition accuracy of 72% was obtained.