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| A Paper Defects Detection Method Based on Machine Vision |
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| DOI：10.11981/j.issn.1000-6842.2013.01.48 |
| Key Words:paper defect image； image gray； characteristic value； BP neural network |
| Fund Project:国家重点基础研究发展规划（973计划，2010CB732205）；国家科技支撑计划项目（2007BAF25B00）。 |
| Author Name | Affiliation | | 张学兰1，2 | 1.华南理工大学制浆造纸工程国家重点实验室，广东广州，510640；2.华南理工大学广东省造纸技术与装备公共实验室，广东广州，510640 | | 李 军1，2 | 1.华南理工大学制浆造纸工程国家重点实验室，广东广州，510640；2.华南理工大学广东省造纸技术与装备公共实验室，广东广州，510640 | | 孟范孔3 | 3.华南理工大学机械与汽车工程学院，广东广州，510640 |
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| Abstract: |
| A new paper defects recognition algorithm based on image gray transformation and BP neural network was put forward.The paper image was preprocessed, then the paper defects characteristic value was extracted, finally, the BP neural network was used to classify paper defects. Experimental results showed that this algorithm could successfully recognize a paper image that contains holes, spots and folds. The precision of the performance of the system reached 93.8%． |
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