TY - GEN
T1 - Design of real-time steel bars recognition system based on machine vision
AU - Zhao, Jianyu
AU - Xia, Xiangxiang
AU - Wang, Haodi
AU - Kong, Siwei
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.
PY - 2016/12/13
Y1 - 2016/12/13
N2 - Currently, the bar counting is mainly completed by manpower, this method can make the workers fatigue easily, besides error counting, which can not guarantee the accurateness of packaging and match the high level of automatic equipment of steel rolling production line. To solve these problems, using machine vision and computer image processing technology, we design a real-time steel bars system. First we build up the hardware and software structure of system. Then we introduce the detailed working process, and design the detailed image processing algorithm. The results of experiments demonstrate the accuracy of bar counting in a single frame is up to 96% in this system, and its processing speed can meet the real-time requirements. © 2016 IEEE.
AB - Currently, the bar counting is mainly completed by manpower, this method can make the workers fatigue easily, besides error counting, which can not guarantee the accurateness of packaging and match the high level of automatic equipment of steel rolling production line. To solve these problems, using machine vision and computer image processing technology, we design a real-time steel bars system. First we build up the hardware and software structure of system. Then we introduce the detailed working process, and design the detailed image processing algorithm. The results of experiments demonstrate the accuracy of bar counting in a single frame is up to 96% in this system, and its processing speed can meet the real-time requirements. © 2016 IEEE.
KW - Bars recognition
KW - Image segmentation
KW - Machine vision
KW - Real-time
UR - http://www.scopus.com/inward/record.url?scp=85010390694&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85010390694&origin=recordpage
U2 - 10.1109/IHMSC.2016.75
DO - 10.1109/IHMSC.2016.75
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781509007684
VL - 1
T3 - Proceedings - 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
SP - 505
EP - 509
BT - Proceedings - 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
PB - IEEE
T2 - 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2016
Y2 - 11 September 2016 through 12 September 2016
ER -