TY - GEN
T1 - Identification of Coal and Gangue via Millimeter Wave Imaging with Corresponding Optical Photo
AU - Wang, Shuoguang
AU - Xing, Guangnan
AU - Jing, Handan
AU - Li, Shiyong
AU - An, Qiang
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The identification of the coal and gangue are essential in the coal preparation process. Combining with imaging processing technologies (like de-noising, enhancement, and feature extraction), the imaging-based technology accomplishes the coal-gangue identification while avoiding the shortcomings of traditional methods (radiation, pollution, etc). However, environment factors (light, dust, temperature, etc) would greatly influence the identification results. A millimeter imaging combining with the optical photo technique is proposed for the recognition of coal and gangue. First, the millimeter wave (MMW) imaging results of the ores are achieved by the Range Migration Algorithm (RMA). Second, the profiles of the ores in the corresponding optical photo are adopted by the Seeded Region Growing (SRG), which are transferred to the MMW images for further identification. Furthermore, a simple threshold-based strategy is applied to compute the coal ratio of each ore to achieve the identification. The experimental results demonstrate that the proposed strategy is of great potential for nondestructive identification of coal from the gangue.
AB - The identification of the coal and gangue are essential in the coal preparation process. Combining with imaging processing technologies (like de-noising, enhancement, and feature extraction), the imaging-based technology accomplishes the coal-gangue identification while avoiding the shortcomings of traditional methods (radiation, pollution, etc). However, environment factors (light, dust, temperature, etc) would greatly influence the identification results. A millimeter imaging combining with the optical photo technique is proposed for the recognition of coal and gangue. First, the millimeter wave (MMW) imaging results of the ores are achieved by the Range Migration Algorithm (RMA). Second, the profiles of the ores in the corresponding optical photo are adopted by the Seeded Region Growing (SRG), which are transferred to the MMW images for further identification. Furthermore, a simple threshold-based strategy is applied to compute the coal ratio of each ore to achieve the identification. The experimental results demonstrate that the proposed strategy is of great potential for nondestructive identification of coal from the gangue.
KW - coal and gangue identification
KW - millimeter wave imaging
KW - range migration algorithm
KW - seed region growing
UR - http://www.scopus.com/inward/record.url?scp=85181074691&partnerID=8YFLogxK
U2 - 10.1109/Radar53847.2021.10028608
DO - 10.1109/Radar53847.2021.10028608
M3 - Conference contribution
AN - SCOPUS:85181074691
T3 - Proceedings of the IEEE Radar Conference
SP - 1310
EP - 1313
BT - 2021 CIE International Conference on Radar, Radar 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 CIE International Conference on Radar, Radar 2021
Y2 - 15 December 2021 through 19 December 2021
ER -