Citation

Ghazali, Muhammad Faiz and Wong, Lai Kuan and See, John Su Yang (2016) Automatic Detection and Counting of Circular and Rectangular Steel Bars. In: 9th International Conference on Robotic, Vision, Signal Processing and Power Applications. Springer, pp. 199-207. ISBN 978-981-10-1719-3, 978-981-10-1721-6

Text 86.pdf Restricted to Repository staff only Download (544kB)

Abstract

The steel industry heavily relies on manual labor and the use of photoelectric sensors and complex counting machines to count steel bars. In the last decade, research on the automatic detection and counting of steel bars by using image processing and computer vision techniques have seen much progress. Nevertheless, most of past research focused mainly on circular shaped steel bars from a direct frontal camera angle. In this paper, we propose a method that is adaptable to both circular and rectangular shaped steel bars, and robust towards different camera angles and lighting intensity. The captured digital image first undergoes an essential pre-processing stage followed by edge detection which extracts the steel bar edges. For circular shaped steel bars, we apply Hough Transform followed by a post-process while the rectangular ones can be accurately found based on a series of morphological operations. Experiments conducted on a variety of challenging conditions demonstrate the capability of our approach to a good measure of success.

Item Type:	Book Section
Uncontrolled Keywords:	Steel bars, steel bar detection, steel bar counting, circular steel bar, rectangular steel bar
Subjects:	T Technology > TS Manufactures > TS200-770 Metal manufactures. Metalworking
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	26 Nov 2020 11:35
Last Modified:	26 Nov 2020 11:35
URII:	http://shdl.mmu.edu.my/id/eprint/7119

Downloads

Edit (login required)