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第30届中国控制与决策会议

作者： Fei Dai Baojie Fan Yan Peng Academy of Automation Nanjing University of Posts and Telecommunications School of Mechatronic Engineering and Automation Shanghai University

In order to solve the problem in image haze removal algorithms based on dark channel prior like color distortion and blurred image edge information, an improved image haze removal algorithm based on blockwise processing is proposed. Firstly, we choose lab color space instead of RGB color space. Then, bilateral filtering is used to preserve edge smoothly and refine the transmission map. Finally, we set the tolerance for blockwise processing to remove color distortion problem. The results demonstrate that, the new algorithm we proposed can successfully solve the problems like color distortion and blurred image edge information in image removal based on dark channel prior, the algorithm’s running time is greatly reduced simultaneously.

关键词： Image haze removal Dark channel prior lab color space Bilateral filtering Tolerance Blockwise processing

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Monocular vision for variable spray control system

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International Journal of Agricultural and Biological Engineering 2022年第6期15卷 206-215页

作者： Daozong Sun Weikang Liu Runmei Luo Xurui Zhan Zehong Chen Tao Wei Xinrui Wang Xiuyun Xue Zhen Li Shuran Song College of Electronic Engineering(College of Artificial Intelligence) South China Agricultural UniversityGuangzhou 510642China Guangdong Engineering Research Center for Monitoring Agricultural Information Guangzhou 510642China National Citrus Industry Technology System Mechanization Research laboratory Guangzhou 510642C

The monocular vision-based system can obtain the leaf wall area characterizing the canopy parameter for online detection and real-time variable spraying,aiming to improve the accuracy of orchard spraying equipment and the utilization efficiency of *** study established a spraying system,in which canopy parameters were collected by monocular vision,and the spray volume decision coefficient was constructed by the leaf wall area and the L^(*)value in International Commission on Illumination lab color space to control the duty cycle of each solenoid valve to achieve variable *** spray flow models were designed to determine the spray volume decision *** coefficients of determination of the spray volumes with the duty cycle range of 15%to 65%were all over 94 and the error of the leaf wall area values obtained using the improved super green algorithm(calculated as ExG=2.1G–1.1R–1.1B)was only 0.5%.The test showed that there is a negative relationship between canopy denseness and L^(*),and the value of L^(*)is smaller in the dense area compared with the sparse area;the actual flow generated by the system is similar to the theoretical flow when the duty cycle is 65%.The field validation tests showed that the variable spraying system could refine the droplet size and increase the droplet density to a certain extent with the same coverage rate,which had advantages over the continuous *** terms of droplet deposition,DV0.1 and DV0.9 were reduced by 2μm and 18μm,respectively,and the increase of droplet density to 75 droplets/*** the same time,the improvement of droplet distribution uniformity and droplet penetration by 16%and 3%,*** with continuous spraying,variable spraying can achieve 55.64%*** study demonstrates the feasibility of monocular vision in guiding spraying operations and provides a reference for the use of monocular vision in plant protection operations.

关键词： monocular vision leaf wall area lab color space pulse width modulation variable sprayi

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Novel method for the visual navigation path detection of jujube harvester autopilot based on image processing

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International Journal of Agricultural and Biological Engineering 2023年第5期16卷 189-197页

作者： Xiongchu Zhang Bingqi Chen Jingbin Li Xin Fang Congli Zhang Shubo Peng Yongzheng Li College of Engineering China Agricultural UniversityBeijing 100083China College of Mechanical and Electrical Engineering Shihezi UniversityShihezi 832003China

To realize automatic harvesting of the jujube,the jujube harvester was designed and *** achieving the jujube harvester autopilot,a novel algorithm for visual navigation path detection was *** centerline of tree row lines was taken as the navigation *** method included four main parts:image preprocessing,image segmentation,tree row lines access,and navigation path *** methods of threshold segmentation,noise removal,and border smoothing were utilized on the image in lab color space for the image *** least square method was employed to fit the tree row lines,and the centerline was obtained as the navigation *** results indicated that the average false detection rate was 3.98%,and the average detection speed was 41 *** algorithm meets the requirements of the jujube harvester autopilot in terms of accuracy and *** also can lay the foundation for accomplishing the jujube harvester vision-based autopilot.

关键词： visual navigation path jujube orchards image processing lab color space seed region growing

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