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Design and Implementation of Agricultural Information Management System Based on Mobile GIS2023 International Conference on Computer Science and Automation Technology (CSAT)10.1109/CSAT61646.2023.00060

Performance Analysis of Target Information Recognition System for Agricultural Robots

Yun Ji, Rajeev Kumar, Daljeet Singh, Maninder Singh

Source Title: International Journal of Agricultural and Environmental Information Systems (IJAEIS)12(2)

ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781799861591|DOI: 10.4018/IJAEIS.20210401.oa4

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MLA

Ji, Yun, et al. "Performance Analysis of Target Information Recognition System for Agricultural Robots." IJAEIS vol.12, no.2 2021: pp.49-60. http://doi.org/10.4018/IJAEIS.20210401.oa4

APA

Ji, Y., Kumar, R., Singh, D., & Singh, M. (2021). Performance Analysis of Target Information Recognition System for Agricultural Robots. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 12(2), 49-60. http://doi.org/10.4018/IJAEIS.20210401.oa4

Chicago

Ji, Yun, et al. "Performance Analysis of Target Information Recognition System for Agricultural Robots," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 12, no.2: 49-60. http://doi.org/10.4018/IJAEIS.20210401.oa4

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Abstract

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production monitoring and prediction tasks, the target information recognition approach, and visual servo decision making. The results obtained from the proposed system show that using the region combination features of image 2D histogram as the decision-making basis, the accurate and rapid indirect identification and positioning of crop seedlings can be accomplished while skipping the complex process of accurately identifying crops and weeds. The algorithm performs reasonably good as the time of target recognition in the prototype system is found to be less than 16 ms, and the average accurate recognition rate of 97.43% is achieved. The benefits of the proposed system are the continuous improvement of the quality of agricultural products, the rise of production efficiency, and the increase of economic benefits.