Plug hole positioning and seedling shortage detecting system on automatic seedling supplementing test-bed for vegetable plug seedlings

WANG Yongwei1 XIAO Xize1 LIANG Xifeng2,3 WANG Jun1 WU Chuanyu3 XU Jiankang4

(1.School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China 310058)
(2.College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou, China 310018)
(3.College of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, China 310018)
(4.Yongkang Quality and Technology Supervision and Inspection Center, Yongkang, China 321300)

【Abstract】The seeds cannot fully sprout owing to the seed quality, sowing precision, and environmental difference. In order to get the accurate information of the null plug holes and the boundary of plug holes and provide the basis for automatic seedling supplement device, an automatic seedling supplementing test-bed was developed with aseedling shortage detecting system and a seedling supplementing system as core components. The seedling shortage detection system was composed of a hardware system for image processing, which included a CMOS industrial camera, a controller, and a computer, and a software system programmed in MATLAB. The color images (RGB images) of Arabidopsis thaliana plug seedlings with the ages of 25 and 35 days were acquired with the automatic seedling supplementing test-bed. The gray-level images of seedlings and plug holes were obtained by graying the color images applying different linear transformations to three color components of R, G, and B. Applying Otsu algorithm, binary images of the gray-level images of seedlings were obtained through thresholding. Then, the morphological corrosion operation and dilation operation of the binary images were carried out by the disk 2 × 2 type structure operator. By marking single connected domain, analyzing the characteristics of connected domain and removing the isolated area, the noises in the binary images were removed and the feature images of the seedlings were extracted from the background effectively. The feature images of plug tray were acquired by removing the feature images of plug seedlings from that of the plug tray according to the extracted seedling information and denoising. Then, statistics on the peak value, peak width, and standardizing structure of plug tray were made according to the row and column pixel of binary images of plug trays, so that the boundary of plug holes were determined accurately. The statistics of the pixel of the seedling image in each plug hole were made to determine whether the hole was short of seedlings according to the feature images of the seedlings, the position, and the boundary information of the plug holes. The results showed that the statistics values of the seedling image pixel of the plug holes with the A. thaliana plug seedlings of 25 and 35 days were 1 895 to 4 572, and 3 386 to 8 710, respectively, while the statistics value of the seedlings image pixel of the plug holes without seedlings was 0. There was significant difference in the statistics value of the seedling image pixels between the plug holes with seedlings and the null plug holes. The testing results of the missing plug tray hole were the same as the actual situation, and the statistical value of seedling pixels corresponded to the projection area of stem and leaf. According to the threshold values of seedlings at different growth stages, the undeveloped seedlings could be marked for removing, so the seedling early stage was the super time for the detection of the null plug hole and the determination of the undeveloped seedlings. The accuracy of judging the null plug holes and the seedling holes with the A. thaliana plug seedlings of 25 and 35 days was all 100% applying the detection device. The accurate determination of position of the null plug hole provides basis for automatic supplementing system taking out the substrate without seedlings, removing dysplasia seedlings and supplementing healthy seedlings with the same age.

【Keywords】 agricultural machinery; transplanting; image processing; detection for the seedling shortage; plug hole positioning;

【DOI】

【Funds】 Fundamental Research Funds for the Central Universities Dabeinong Discipline-Developing and Talents-Cultivating Fund of Zhejiang University National Natural Science Foundation of China (51505454) National High Technology Research and Development Program of China (863 Program) (2012AA10A504)

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(Translated by LIU T)

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This Article

ISSN:1002-6819

CN: 11-2047/S

Vol 34, No. 12, Pages 35-41

June 2018

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Article Outline

Abstract

  • 0 Introduction
  • 1 Test-bed of automatic seedling supplementing for vegetable plug seedlings
  • 2 Feature extraction of plug seedlings and plug tray and determination of seedling shortage
  • 3 Conclusions
  • References