中国造纸学报2013，Vol.28Issue(1)：48-52,5.
一种基于机器视觉的纸病识别方法
A Paper Defects Detection Method Based on Machine Vision
摘要
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%.关键词
纸病图像/图像灰度/特征值/BP神经网络Key words
paper defect image/ image gray/ characteristic value/ BP neural network分类
轻工纺织引用本文复制引用
张学兰,李军,孟范孔..一种基于机器视觉的纸病识别方法[J].中国造纸学报,2013,28(1):48-52,5.基金项目
国家重点基础研究发展规划(973计划,2010CB732205) （973计划,2010CB732205）
国家科技支撑计划项目(2007BAF25B00). （2007BAF25B00）
