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焊接缺陷磁光成像纹理特征GLCM-Gabor识别方法

蓝重洲,高向东,马女杰,张南峰

蓝重洲,高向东,马女杰,张南峰. 焊接缺陷磁光成像纹理特征GLCM-Gabor识别方法[J]. 焊接学报, 2018, 39(6). DOI: 10.12073/j.hjxb.2018390157
引用本文: 蓝重洲,高向东,马女杰,张南峰. 焊接缺陷磁光成像纹理特征GLCM-Gabor识别方法[J]. 焊接学报, 2018, 39(6). DOI: 10.12073/j.hjxb.2018390157

焊接缺陷磁光成像纹理特征GLCM-Gabor识别方法

  • [1] 刘贵民, 马丽丽. 无损检测技术[M]. 国防工业出版社, 2010.[2] 胡文刚, 刚 铁. 基于超声信号和图像融合的焊缝缺陷识别[J]. 焊接学报, 2013, 34(4): 53-56.Hu Wengang, Gang Tie. Recognition of weld flaw based on feature fusion of ultrasonic signal and image[J]. Transactions of the China Welding Institution, 2013, 34(4): 53-56.[3] Gao X, Chen Y, You D,et al. Detection of micro gap weld joint by using magneto-optical imaging and Kalman filtering compensated with RBF neural network[J]. Mechanical Systems & Signal Processing, 2017, 84: 570-583.[4] 高向东, 黄冠雄, 萧振林, 等. 微间隙焊缝磁光成像小波多尺度融合检测[J]. 焊接学报, 2016, 37(4): 1-4.Gao Xiangdong, Huang Guanxiong, Xiao Zhenlin,et al. Micro weld detection based on magneto-optical imaging and wavelet multi-scale fusion[J]. Transactions of the China Welding Institution, 2016, 37(4): 1-4.[5] Richert H, Schmidt H, Lindner S,et al. Dynamic magneto-optical imaging of domains in grain-oriented electrical steel[J]. Steel Research International, 2016, 87(2): 232-240.[6] 吴和静. 基于二维Gabor滤波器的掌纹识别[D]. 吉林大学, 2007.
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  • 收稿日期:  2017-06-19

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