Middle Scale Tiny Components Online Detection Based on Machine Vision

DOI

10.2991/icadme-16.2016.135How to use a DOI?

Keywords

Middle scale component, Machine vision, Sub-pixel localization, Real time

Abstract

For middle scale components online detection, a chip online detection method was proposed based on machine vision, the hardware platform was built, the software system was developed, and a new sub-pixel localization algorithm for line and arc was put forward. Through image preprocessing, edge detection and the deletion of small area objects, the target area of chip image was obtained. Through sub-pixel location, the detection precision and accuracy can be improved. Comparing the detection parameters and parameter indexes, the functions of eliminating the unqualified product and determining the positive and negative polarity, center position and rotation angle of qualified product are well implemented. The detection time is less than 1s, achieving real time detection requirements.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Q.M. Liu
AU  - X. Li
AU  - X. Wu
AU  - L. Zhang
PY  - 2017/07
DA  - 2017/07
TI  - Middle Scale Tiny Components Online Detection Based on Machine Vision
BT  - Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 750
EP  - 754
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-16.2016.135
DO  - 10.2991/icadme-16.2016.135
ID  - Liu2017/07
ER  -