Scene character detection and recognition based on multiple hypotheses framework

To handle the diversity of scene characters, we propose a multiple hypotheses framework which consists of an image operator set module, an optical character recognition (OCR) module, and an integration module. Image operators detect multiple suspicious character areas. The OCR engine is then applied to each detected area and returns multiple candidates with weight values for future integration. Without the aid of heuristic constraints on area, aspect ratio or color etc., the integration module prunes the redundant detection and pads the missing detection based on the outputs of OCR. The experimental results demonstrate that the whole multiple hypotheses outperforms each operator's hypotheses and be comparable with existing methods in terms of recall, precision, F-measure and recognition rate.