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| Paper Defects Offline Static Identification Based on Naive Bayes Classifier |
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| DOI： |
| Key Words:naive Bayes Classifier； conditional probability； posterior probability； paper defects offline static identification |
| Fund Project:陕西省科技统筹创新工程计划项目（2012KTCQ01-19）；陕西省科技攻关项目(2011K06-06)；陕西省教育厅专项科研计划项目(2010JK420)；陕西科技大学科研启动基金(BJ10-05)；陕西科技大学学术骨干培育计划(XSG2010010)。 |
| Author Name | Affiliation | | 院金彪1 | 1.陕西科技大学电气与信息工程学院，陕西西安，710021 | | 周 强1 | 1.陕西科技大学电气与信息工程学院，陕西西安，710021 | | 郑海英2 | 2.察右中旗第一中学，内蒙古乌兰察布市，013550 | | 郭文强１ | 1.陕西科技大学电气与信息工程学院，陕西西安，710021 | | 汤 伟１ | 1.陕西科技大学电气与信息工程学院，陕西西安，710021 |
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| Abstract: |
| Considering the problems of weak algorithm versatility, poor robustness of current paper defects identification methods. This paper proposed a method of using probability value to identify the category of the paper defects. This method obtained the prior probability distribution and conditional probability value of paper defects through training samples. These values were used to posterior probability calculation which could determine the type of paper defects, to simplify the computation and meet the real-time requirements of paper defect identification process, meanwhile the application of Bayesian Classifier with the smallest error rate characteristic could guarantee the accuracy requirement of the identification. Experiments results showed that this method could effectively and quickly identify defects on paper with strong versatility． |
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