Expanding Recognizable Distorted Characters Using Self-Corrective Recognition

Large datasets are always demanded for better recognition performance. However, it is not easy to produce them because costly and slow human operators have been necessary for labeling. In the current paper, in order to resolve the problem on yielding large datasets, we propose a scenario for automatic labeling based on the self-corrective recognition algorithm. The strong point of the proposed method is the capability of expanding recognizable distorted characters unlike existing methods. In the experiments, we show a possibility to realize automatic labeling by the method.