Precision Constrained Gaussian Model for Online Handwritten Jamo Character Recognition

It is important to extract pattern´s feaure and recognize them by proper model in pattern classification. In this paper, we propose the modified LDA to compress the extracted feature, and design the classifier with Precision Constrained Gaussian Model. A series of experiments are offered and the experimental result shows that our PCGM can achieve a much better generalization and MLDA has a better performance than LDA in classification.