Handlebar appearance inspection algorithm based on two-direction trace and check

DOI

10.2991/nceece-15.2016.94How to use a DOI?

Keywords

product appearance; image recognition; image preprocessing; dark grain extraction

Abstract

High automatically industry production is an inevitable trend in the development of modern factory. Based on objects of precise, efficient and intelligent manufacturing and replacing heavy manual labor to lower the high error rate., this paper proposes a new product appearance dark grain detection algorithm. Firstly, the Gauss function is adapted to image preprocessing operations including noise filtering, pixel binarization, state judge, division and so on; then, “left-bottom detection" and "right-bottom detection" are combined to detect and extract the dark grain characteristics of products. The experimental results show that this two-direction combined detection algorithm described in this paper is effective in practical application. Conclusion is that the proposed method can be widely applied in product appearance detection field.

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  - Jingfei Zhang
AU  - KaiJin Qiu
PY  - 2015/12
DA  - 2015/12
TI  - Handlebar appearance inspection algorithm based on two-direction trace and check
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 482
EP  - 487
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.94
DO  - 10.2991/nceece-15.2016.94
ID  - Zhang2015/12
ER  -