A SVM and SLIC Based Detection Method for Paddy Field Boundary Line
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200000, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(9), 2610; https://doi.org/10.3390/s20092610
Received: 7 April 2020
/
Revised: 23 April 2020
/
Accepted: 29 April 2020
/
Published: 3 May 2020
(This article belongs to the Section Intelligent Sensors)
Visual based route and boundary detection is a key technology in agricultural automatic navigation systems. The variable illumination and lack of training samples has a bad effect on visual route detection in unstructured farmland environments. In order to improve the robustness of the boundary detection under different illumination conditions, an image segmentation algorithm based on support vector machine was proposed. A superpixel segmentation algorithm was adopted to solve the lack of training samples for a support vector machine. A sufficient number of superpixel samples were selected for extraction of color and texture features, thus a 19-dimensional feature vector was formed. Then, the support vector machine model was trained and used to identify the paddy ridge field in the new picture. The recognition F1 score can reach 90.7%. Finally, Hough transform detection was used to extract the boundary of the ridge field. The total running time of the proposed algorithm is within 0.8 s and can meet the real-time requirements of agricultural machinery.
View Full-Text
Keywords:
field boundary line detection; vision in agriculture; support vector machine line detection; superpixel segmentation algorithm
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Li, Y.; Hong, Z.; Cai, D.; Huang, Y.; Gong, L.; Liu, C. A SVM and SLIC Based Detection Method for Paddy Field Boundary Line. Sensors 2020, 20, 2610. https://doi.org/10.3390/s20092610
AMA Style
Li Y, Hong Z, Cai D, Huang Y, Gong L, Liu C. A SVM and SLIC Based Detection Method for Paddy Field Boundary Line. Sensors. 2020; 20(9):2610. https://doi.org/10.3390/s20092610
Chicago/Turabian StyleLi, Yanming, Zijia Hong, Daoqing Cai, Yixiang Huang, Liang Gong, and Chengliang Liu. 2020. "A SVM and SLIC Based Detection Method for Paddy Field Boundary Line" Sensors 20, no. 9: 2610. https://doi.org/10.3390/s20092610
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
