Research Article
A Machine Vision Based Automatic Optical Inspection System for Detecting Defects of Rubber Keypads of Scanning Machine
@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
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.
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.
