Method of character recognition algorithm based on AdaBoost and its application

To solve the contradiction of speed and accuracy of commonly used methods of character recognition,an improved AdaBoost recognition algorithm is proposed.Based on full dichotomy of the character set by employing prior knowledge,cascaded classifiers are trained separately,generating high recognition accuracy by full sample learning.Because of high computation load,its’ hard to meet the real-time demand of industrial application by soft implementation of AdaBoost.Based on the similarity of mass multiply accumulation operation,parallel architecture based on FPGA is proposed.Application in online printing quality detection system demonstrated its reco-gnition accuracy and can meet the real-time requirements.