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带钢表面缺陷图像小波融合方法
引用本文:王永慧,颜云辉,吴艳萍,梁惠升.带钢表面缺陷图像小波融合方法[J].东北大学学报(自然科学版),2009,30(5):728-732.
作者姓名:王永慧  颜云辉  吴艳萍  梁惠升
作者单位:东北大学机械工程与自动化学院,辽宁,沈阳,110004
基金项目:国家高技术研究发展计划(863计划),国家自然科学基金和上海宝钢集团公司联合资助项目 
摘    要:采用两个CCD图像传感器在多种采集方式下获得不同缺陷图像,运用小波变换法对缺陷图像进行融合,结合带钢表面缺陷特征对融合算法和规则进行了探讨,并对融合后的缺陷图像质量进行评价.实验结果显示了小波融合方法的优越性,该方法能更全面、更准确、更大限度地获得缺陷图像信息,解决了单一CCD缺陷采集模式下存在的缺陷特征丢失问题,为后续的缺陷识别与分类提供有效、可靠的数据支持.

关 键 词:小波变换  图像融合  表面缺陷  带钢  

Image Fusion Based on Wavelet Transformation for Strip Steel Surface Defects
WANG Yong-hui,YAN Yun-hui,WU Yan-ping,LIANG Hui-sheng.Image Fusion Based on Wavelet Transformation for Strip Steel Surface Defects[J].Journal of Northeastern University(Natural Science),2009,30(5):728-732.
Authors:WANG Yong-hui  YAN Yun-hui  WU Yan-ping  LIANG Hui-sheng
Institution:WANG Yong-hui,YAN Yun-hui,WU Yan-ping,LIANG Hui-sheng (School of Mechanical Engineering & Automation,Northeastern University,Shenyang 110004,China.)
Abstract:Two CCD camera sensors were applied to the same object to acquire different defect images on strip steel surface in several ways,then the images were implemented to those defects through wavelet transformation.The fusion algorithm and rules based on the abstract features from the real surface defects are discussed with the quality of defect images after fusion evaluated.Experimental results showed obviously the superiority of the approach mentioned above because it can acquire more accurate defect image dat...
Keywords:wavelet transformation  image fusion  surface defect  strip steel  
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