关键词: 修正的二次判别函数, 深度玻尔兹曼机, 脱机手写汉字识别

Abstract:

As to the low accuracy of offline handwritten Chinese character recognition, a cascade classifier model based on Modified Quadratic Discriminant Function（MQDF） and Deep Boltzmann Machine（DBM） is proposed. The main idea behind the model is that MQDF and DBM can complement each other in features extraction and classification mechanisms. Firstly it recognitzes and gets the result using MQDF, and calculates the generalized confidence of the recognition result. If the confidence meets the requirement, the recognition result can be as the final result directly output; otherwise, combining with DBM to make recognition again, and the result will be taken as the final recognition result. Experimental results show that using MQDF-DBM model can achieve higher accuracy than using MQDF and DBM model alone, and the recognition speed is faster than DBM.

Key words: Modified Quadratic Discriminant Function（MQDF）, Deep Boltzmann Machine（DBM）, offline handwritten Chinese character recognition