inis 19(18): e3

Research Article

A Machine Vision Based Automatic Optical Inspection System for Detecting Defects of Rubber Keypads of Scanning Machine

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  • @ARTICLE{10.4108/eai.28-3-2019.157121,
    author={Huan Ngoc Le and Ngoc Vuong Bao Tu},
    title={A Machine Vision Based Automatic Optical Inspection System for Detecting Defects of Rubber Keypads of Scanning Machine},
    journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
    volume={6},
    number={18},
    publisher={EAI},
    journal_a={INIS},
    year={2019},
    month={3},
    keywords={Detect defects, Computer vision, 2D calibration, Rubber keypad, AOI},
    doi={10.4108/eai.28-3-2019.157121}
}
  • Huan Ngoc Le
    Ngoc Vuong Bao Tu
    Year: 2019
    A Machine Vision Based Automatic Optical Inspection System for Detecting Defects of Rubber Keypads of Scanning Machine
    INIS
    EAI
    DOI: 10.4108/eai.28-3-2019.157121
Huan Ngoc Le1,*, Ngoc Vuong Bao Tu2
  • 1: Mechanical & Mechatronics Department, Eastern International University, Nam Ky Khoi Nghia Street, Hoa Phu Ward, New city, Binh Duong Province, Viet Nam
  • 2: Master’s student, International University, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Viet Nam
*Contact email: huan.le@eiu.edu.vn

Abstract

In order to detect defective rubber keypads, factories have to devote massive manpower and financial resources. In this paper, a vision-based system for the detection of a number of rubber keypad defects is designed and developed. To improve the lens distortion rectification, a novel, easy calibration method using image local transformations defined by both sets of points that are detected in the distorted image and the undistorted ones without using any model for a wideangle and low- cost lens camera was proposed. The system detects the defects of 14 different types of rubber keypads quickly (~within about 1.8 seconds) and accurately even with a normal laptop and a low-price webcam.

Keywords
Detect defects, Computer vision, 2D calibration, Rubber keypad, AOI
Received
2019-02-19
Accepted
2019-03-22
Published
2019-03-28
Publisher
EAI
http://dx.doi.org/10.4108/eai.28-3-2019.157121

Copyright © 2019 Huan Ngoc Le et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.