On-line Chinese Character Recognition System for Overlapping Samples

We proposed a new process strategy for on-line handwriting Chinese Character recognition and applied it to overlapping samples. On one hand, those samples are evaluated on stroke level by support vector machine, on the other hand, we do character level evaluation basing on a character pair search model. Then a merging strategy was proposed to filter out correct segmentation positions. We test our strategy on samples from real context, verifying that our strategy performs better than traditional over-segmentation and merging method.