Ultrasonic image restoration based on support vector machine for surfacing interface testing

被引：0
|
作者：
高双胜
刚铁
迟大钊
机构：
[1] State Key Laboratory of Advanced Welding Production Technology Harbin Institute of Technology
[2] State Key Laboratory of Advanced Welding Production Technology Harbin Institute of Technology
[3] Harbin 150001
来源：
China Welding | 2007年 / 02期
关键词：
ultrasonic C-scan; surfacing interface; support vector regression (SVR); image restoration;
D O I：
暂无
中图分类号：
TG441.7 [焊接缺陷及质量检查];
学科分类号：
080201 ; 080503 ;
摘要：
In order to restore the degraded ultrasonic C-scan image for testing surfacing interface, a method based on support vector regression (SVR) network is proposed. By using the image of a simulating defect, the network is trained and a mapping relationship between the degraded and restored image is founded. The degraded C-scan image of Cu-Steel surfacing interface is processed by the trained network and improved image is obtained. The result shows that the method can effectively suppress the noise and deblur the defect edge in the image, and provide technique support for quality and reliability evaluation of the surfacing weld.
引用
收藏
页码：27 / 30
页数：4
相关论文
共 50 条
  • [1] Omnidirection Image Restoration Using a Support Vector Machine
    Liu, Liqun
    Cao, Zuoliang
    [J]. 2008 INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, VOLS 1-4, 2008, : 606 - 611
  • [2] Support Vector Regression based Image Restoration
    Sa, Pankaj Kumar
    Majhi, Banshidhar
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013), 2013,
  • [3] Ultrasonic image classification based on support vector machine with two independent component features
    Chen, Weishi
    Liu, Tiejun
    Wang, Baofa
    [J]. COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 62 (07) : 2696 - 2703
  • [4] Image Segmentation Based on Support Vector Machine
    Wang, Xuejun
    Wang, Shuang
    Zhu, Yubin
    Meng, Xiangyi
    [J]. PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012), 2012, : 202 - 206
  • [5] Image Segmentation Based on Support Vector Machine
    徐海祥
    朱光喜
    田金文
    张翔
    彭复员
    [J]. Journal of Electronic Science and Technology, 2005, (03) : 226 - 230
  • [6] IMAGE ACCELERATION RESTORATION ALGORITHM FOR TURBULENCE-DEGRADED IMAGES BASED ON SUPPORT VECTOR MACHINE
    Li Ming
    Yang Jie
    [J]. JOURNAL OF INFRARED AND MILLIMETER WAVES, 2009, 28 (06) : 472 - 475
  • [7] Adaptive split spectrum processing technique based on support vector machine for ultrasonic nondestructive testing
    Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Institute of Advanced Manufacturing Engineering, Zhejiang University, Hangzhou 310027, China
    [J]. Zhejiang Daxue Xuebao (Gongxue Ban), 2008, 8 (1423-1427):
  • [8] Image denoising based on wavelet support vector machine
    Zhang, Shaoming
    Chen, Ying
    [J]. 2006 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PTS 1 AND 2, PROCEEDINGS, 2006, : 1809 - 1812
  • [9] Image Classification Based on Fuzzy Support Vector Machine
    Li, Jianming
    Huang, Shuguang
    He, Rongsheng
    Qian, Kunming
    [J]. PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 1, 2008, : 68 - 71
  • [10] Image denoising based on wavelet support vector machine
    Zhang, Shaoming
    Chen, Ying
    [J]. COMPUTATIONAL INTELLIGENCE AND SECURITY, 2007, 4456 : 963 - 971
12345