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Article

Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus

by 1,2,*, 1, 2 and 1
1
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
2
School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai 201209, China
*
Author to whom correspondence should be addressed.
Academic Editor: Yiannis Ampatzidis
Sensors 2022, 22(10), 3946; https://doi.org/10.3390/s22103946
Received: 20 March 2022 / Revised: 16 May 2022 / Accepted: 19 May 2022 / Published: 23 May 2022
(This article belongs to the Special Issue AI-Based Sensors and Sensing Systems for Smart Agriculture)
The accurate identification of overlapping Agaricus bisporus in a factory environment is one of the challenges faced by automated picking. In order to better segment the complex adhesion between Agaricus bisporus, this paper proposes a segmentation recognition algorithm for overlapping Agaricus bisporus. This algorithm calculates the global gradient threshold and divides the image according to the image edge gradient feature to obtain the binary image. Then, the binary image is filtered and morphologically processed, and the contour of the overlapping Agaricus bisporus area is obtained by edge detection in the Canny operator, the convex hull and concave area are extracted for polygon simplification, and the vertices are extracted using Harris corner detection to determine the segmentation point. After dividing the contour fragments by the dividing point, the branch definition algorithm is used to merge and group all the contours of the same Agaricus bisporus. Finally, the least squares ellipse fitting algorithm and the minimum distance circle fitting algorithm are used to reconstruct the outline of Agaricus bisporus, and the demand information of Agaricus bisporus picking is obtained. The experimental results show that this method can effectively overcome the influence of uneven illumination during image acquisition and be more adaptive to complex planting environments. The recognition rate of Agaricus bisporus in overlapping situations is more than 96%, and the average coordinate deviation rate of the algorithm is less than 1.59%. View Full-Text
Keywords: overlapping; Agaricus bisporus; segmentation recognition algorithm; image edge gradient feature; contour segmentation; grouping recognition overlapping; Agaricus bisporus; segmentation recognition algorithm; image edge gradient feature; contour segmentation; grouping recognition
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MDPI and ACS Style

Yang, S.; Ni, B.; Du, W.; Yu, T. Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus. Sensors 2022, 22, 3946. https://doi.org/10.3390/s22103946

AMA Style

Yang S, Ni B, Du W, Yu T. Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus. Sensors. 2022; 22(10):3946. https://doi.org/10.3390/s22103946

Chicago/Turabian Style

Yang, Shuzhen, Bowen Ni, Wanhe Du, and Tao Yu. 2022. "Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus" Sensors 22, no. 10: 3946. https://doi.org/10.3390/s22103946

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