Prof. Zhiqiang Zheng Profile

Prof. Zhiqiang Zheng

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Proceedings Article | 23 January 2024 Paper

Evaluation of Chabuga Mountain mine after ecological restoration based on remote sensing information processing

Qiyan Li, Zhi Weng, Zhiqiang Zheng

Proceedings Volume 12978, 129782P (2024) https://doi.org/10.1117/12.3019634

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The mining of open pit quarries has caused great damage to the local ecological and geological environment, and the problems such as geological disasters brought about by mining have seriously affected the ecological environment of the local and surrounding areas. Carrying out the corresponding ecological restoration project is the main solution at present. With the completion of the ecological restoration project, the evaluation of the ecological restoration level lacks tracking monitoring and data support. This paper proposes the use of remote sensing imagery to assist in the assessment and detection of the subsequent effect of mountain mine treatment. The satellite image data of Chabuga Mountain in 2019 and 2022 are obtained by remote sensing technology, and the post-ecological restoration images in 2022 are obtained with the field inspection, and the NDVI index, WET index, NDBSI index and LST index are used as reference data, and the principal component analysis method is selected to use the remote sensing ecological index RSEI model as the evaluation standard, so as to compare the results of mountain mine restoration project. Research results show that after the mine repair work, the annual average value of remote sensing ecological index of the mines in the study area was 0.56509 in the middle of the ecological restoration project, which was restored to 0.69072, and the remote sensing ecological index was significantly improved, and the ecological restoration work of mountain mine management was effective.

Proceedings Article | 3 April 2023 Paper

Research on tracking algorithm of milking robot arm based on improved SURF-KCF

Zhiqiang Zheng, Xingyu He, Zhi Weng, Yong Zhang, Caili Gong

Proceedings Volume 12599, 125991M (2023) https://doi.org/10.1117/12.2673475

KEYWORDS: Detection and tracking algorithms, Cameras, Robotics, Imaging systems, Automatic tracking, Target detection, Feature extraction, Matrices

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Aiming at the slow movement and small displacement of dairy cows in the pasture breeding process, but the target scale changes significantly, a SURF-KCF dairy cow teat tracking algorithm is proposed. The original KCF algorithm needs to locate the target before tracking, and the tracking frame cannot be adaptive with the scale of the target. The SURF feature detection is introduced to provide target features for the KCF algorithm to achieve automatic target matching; and the scale estimation strategy is used to achieve scale adaption of cow teat targets. The experimental results show that the proposed improved algorithm achieves cow teat target matching and localization as well as scale adaption of the target area, and long-term stable tracking. Finally, in the laboratory environment, the improved algorithm is applied to the three-degree-of-freedom robotic arm automatic milking robot to realize the cow teat positioning and tracking experiment. When the cow's teat is detected, the robotic arm can automatically move to the position of the cow's teat. Good results have been obtained after testing, which shows the feasibility and effectiveness of the cow teat positioning system.

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