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Open AccessArticle

Navigation Algorithm Based on the Boundary Line of Tillage Soil Combined with Guided Filtering and Improved Anti-Noise Morphology

1
College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
2
Key Laboratory of Intelligent Agricultural Equipment in Jiangsu Province, Nanjing Agricultural University, Nanjing 210031, China
3
NDE Laboratory, College of Engineering, Michigan State University, East Lansing, MI 48824, USA
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(18), 3918; https://doi.org/10.3390/s19183918
Received: 26 August 2019 / Revised: 5 September 2019 / Accepted: 8 September 2019 / Published: 11 September 2019
(This article belongs to the Special Issue Smart Agricultural Applications with Internet of Things)
An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. At first, the two key steps of guided filtering and improved anti-noise morphology navigation line extraction were addressed in detail. Then, the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and its application condition were studied for improving the image-processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption of 0.094   s in comparison with HSV, HIS, and 2R-G-B color spaces. The guided filtering method can effectively distinguish the boundary between the tillage soil compared to other competing vanilla methods such as Tarel, multi-scale retinex, wavelet-based retinex, and homomorphic filtering in spite of having the fastest processing speed of 0.113   s . The extracted soil boundary line of the improved anti-noise morphology algorithm has the best precision and speed compared to other operators such as Sobel, Roberts, Prewitt, and Log. After comparing different sizes of image templates, the optimal template with the size of 140   ×   260 pixels could achieve high-precision vision navigation while the course deviation angle was not more than 7.5 ° . The maximum tractor speed of the optimal template and global template were 51.41   km / h and 27.47   km / h , respectively, which can meet the real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the tillage soil boundary line extracted by the proposed improved anti-noise morphology algorithm, which has broad application prospect. View Full-Text
Keywords: intelligent tractor; vision navigation; improved anti-noise morphology; boundary line; guided filtering intelligent tractor; vision navigation; improved anti-noise morphology; boundary line; guided filtering
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Lu, W.; Zeng, M.; Wang, L.; Luo, H.; Mukherjee, S.; Huang, X.; Deng, Y. Navigation Algorithm Based on the Boundary Line of Tillage Soil Combined with Guided Filtering and Improved Anti-Noise Morphology. Sensors 2019, 19, 3918.

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  • Externally hosted supplementary file 1
    Doi: 10.20944/preprints201907.0248.v1
    Link: https://www.preprints.org/manuscript/201907.0248/v1
    Description: We have revised the paper according to the suggestion of the reviewers . Please find the supplementary file (Revision description). Thanks very much! -- Wei Lu
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