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1 2018

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Feature extraction and template matching algorithm classification for PCB fiducial verification

Fonseka C. L. S. C., Jayasinghe J. A. K. S.

Journal of Achievements in Materials and Manufacturing Engineering

2018

Vol. 86, nr 1

14--32

Purpose: Automatic Optical Inspection (AOI) systems that are extensively used in the industry of Electronics Manufacturing Services (EMS), performs the inspection of Surface Mount Devices (SMD). One of the main tasks of such an AOI system is to align a given PCB to the parameters of the corresponding PCB positioning system by a process called fiducial alignment. However, no detailed analysis has been carried out so far on the methodologies that can be used to have a very precise identification of PCB fiducial points. In our research, we have implemented an AOI system for the inspection of soldering defects of Through Hole Technology (THT) solder joints, which can be integrated to a desktop soldering robotic platform. Such platforms are used in environments where no specific lighting conditions can be provided within a surrounded atmosphere. Therefore, an AOI system that is capable of performing fiducial alignment of any given PCB under varying lighting condition is highly preferred. In this paper, we have presented a detailed analysis on feature extraction and template matching algorithms that can be used to implement a very precise fiducial verification process under normal lighting condition. Design/methodology/approach: A detailed analysis and performance evaluation have been carried out in this paper on prominent image comparison algorithms that are extensively used in the field of image processing. Findings: According to the analysis carried out in this paper, it could be observed that the combination of feature extraction and template matching algorithms gives the best performance in PCB fiducial verification process. Research limitations/implications: This paper only presents the implementation of the front end of our proposed AOI system. The implemented methodologies for the automatic identification of soldering defects will be discussed in separate research papers. Practical implications: The methodologies presented in this paper can be effectively used to implement a very precise and robust PCB fiducial verification process that can be efficiently integrated to a desktop soldering robotic system. Originality/value: This research proposes a very accurate fiducial verification process that can be used under varying lighting conditions on a wide range of different PCB fiducial points.