Degraded Character Recognition by Image Quality Evaluation

The character image quality plays an important role in degraded character recognition which could tell the recognition difficulty. This paper proposed a novel approach to degraded character recognition by three kinds of independent degradation sources. It is composed of two stems: character image quality evaluation, character recognition. Firstly, it presents the dual-evaluation to evaluate the image quality of the input character. Secondly, according to the input evaluation result, the character recognition sub-systems adaptively act on. These sub-systems are trained by character sets whose image qualities are similar to the input´s quality, and have special features and special classifiers respectively. Experiment results demonstrate the proposed approach highly improved the performance of degraded character recognition system.