Text segmentation using Gabor filters for automatic document processing
Machine Vision and Applications - Special issue: document image analysis techniques
A review of recent texture segmentation and feature extraction techniques
CVGIP: Image Understanding
Font Recognition Based on Global Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Writer Identification Using Directional Element Features and Linear Transform
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Writer identification using a hybrid method combining Gabor wavelet and mesh fractal dimension
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Writer identification using fractal dimension of wavelet subbands in gabor domain
Integrated Computer-Aided Engineering
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Many techniques have been reported for handwriting-based writer identification. Most techniques assume that the written text is fixed (e.g., in signature verification). In this paper we attempt to eliminate this assumption by presenting a novel algorithm for automatic text-independent writer identification. Given that the handwriting of different people can often be visually distinctive, we take a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture. In principle this allows us to apply any standard texture recognition algorithm for the task (e.g., the multi-channel Gabor filtering technique). Results of 95.0% accuracy on the classification of 300 test documents from 20 writers are very promising. The method is shown to be robust to noise and contents.