Semi-Automatic Copper Foil Surface Roughness Detection from PCB Microsection Images

被引:0
|
作者
De, Soumya [1 ]
Gafarov, Aleksandr [1 ]
Koledintseva, Marina Y. [1 ]
Stanley, R. Joe [1 ]
Drewniak, James L. [1 ]
Hinaga, Scott [2 ]
机构
[1] Missouri Univ Sci & Technol MS &T, Ctr Electromagnet Compatibil, 4000 Enterprise Dr, Rolla, MO 65401 USA
[2] CISCO Syst Inc, San Jose, CA 95134 USA
来源
2012 IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY (EMC) | 2012年
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Characterization of surface roughness of printed circuit board (PCB) conductors is an important task as a part of signal-integrity analysis on high-speed multi-GHz designs. However, there are no methods to adequately quantify roughness of a signal trace or a power/reference plane layer within finished PCBs. Foil roughness characterization techniques currently available can only be applied to the base foil, prior to its incorporation into a finished board. In a finished PCB, a foil surface is not directly accessible, as it is embedded in the dielectric of the board, and attempting to expose the surface will damage the board and the surface of interest. In this paper, a method of surface roughness quantification from microsectioned samples of PCBs is presented. A small, non-functional area, e. g., a corner of the PCB, can be removed, and the surface roughness of the circuit layers can be assessed without impairing the function of the PCB. In the proposed method, a conductor (a trace or a plane) in the microsectioned sample is first digitally photographed at high magnification. The digital photo obtained is then used as an input to a signal-and image-processing algorithm within a graphical user interface. The GUI-based tool automatically computes and returns the surface roughness values of the layer photographed. The tool enables the user to examine the surface textures of the two sides of the conductor independently. In the case of a trace, the composite value of roughness, based on the entire perimeter of the trace cross-section, can be calculated.
引用
收藏
页码:132 / 137
页数:6
相关论文
共 50 条
  • [41] Semi-Automatic Detection of the Left Ventricular Border
    dos Reis, Maria do Carmo
    da Rocha, Adson F.
    Vasconcelos, Daniel F.
    Espinoza, Bruno L. M.
    Nascimento, Francisco A. de O.
    de Carvalho, Joao L. A.
    Salomoni, Sauro
    Camapum, Juliana F.
    2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 2008, : 218 - +
  • [42] Semi-Automatic Tool for Vitiligo Detection and Analysis
    Neri, Paolo
    Fiaschi, Michela
    Menchini, Giovanni
    JOURNAL OF IMAGING, 2020, 6 (03)
  • [43] Generating Ground Truthed Dataset of Chart Images: Automatic or Semi-automatic?
    Huang, Weihua
    Tan, Chew Lim
    Zhao, Jiuzhou
    GRAPHICS RECOGNITION: RECENT ADVANCES AND NEW OPPORTUNITIES, 2008, 5046 : 266 - 277
  • [44] Semi-automatic Road Extraction from SAR Images Using EKF and PF
    Zhao, J. Q.
    Yang, J.
    Li, P. X.
    Lu, J. M.
    IWIDF 2015, 2015, 47 (W4): : 227 - 230
  • [45] Semi-automatic analysis of rock fracture orientations from borehole wall images
    Thapa, BB
    Hughett, P
    Karasaki, K
    GEOPHYSICS, 1997, 62 (01) : 129 - 137
  • [46] Fatigue properties of copper foil and the evolution of surface roughness
    Oh, Chung-Seog
    Bae, Jong-Sung
    Lee, Hak-Joo
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2008, 9 (04): : 57 - 62
  • [47] A semi-automatic workflow to process images from small mammal camera traps
    Bohner, Hanna
    Kleiven, Eivind Flittie
    Ims, Rolf Anker
    Soininen, Eeva M.
    ECOLOGICAL INFORMATICS, 2023, 76
  • [48] Toward a semi-automatic interpretation of scenes issued from multisensor satellite images
    Ettabaa, K. Saheb
    Farah, I. R.
    Ben Ahmed, Mohamed
    Soulaiman, Bassel
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 3104 - +
  • [49] Semi-automatic extraction of houses with multi right angles from aerial images
    Cheng, Xiran
    Zhang, Jianqing
    Zhang, Zuxun
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2004, 29 (12):
  • [50] Semi-automatic segmentation and surface reconstruction of computed tomography images by using rotoscoping and warping techniques
    Park, S. K.
    Kim, B. K.
    Shin, D. S.
    FOLIA MORPHOLOGICA, 2020, 79 (01) : 156 - 161