Improving Accuracy of Printed Character Recognition Using Hexagonal Zoning of Directional Histogram Feature

Accurate character recognition is still very important for camera based printed document analysis. Due to its inherent conceptual and technical simplicity, conventional recognition strategies relied on features extracted using square block zoning of a character image. In this paper, we propose an isotropic feature extraction method using regular hexagonal zoning and confirm its effectiveness by printed character recognition experiments. A 2% improvement in accuracy was achieved in experiments using gradient features. And the effectiveness of hexagonal zoning for recognition of high stroke count characters and low-resolution characters is confirmed by the experiments.