Tomato identification and picking point location based on YOLOv5

Chengyuan Song; Chao Wang; Jian Song

doi:10.1117/12.2671180

28 April 2023 Tomato identification and picking point location based on YOLOv5

Chengyuan Song, Chao Wang, Jian Song

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126103G (2023) https://doi.org/10.1117/12.2671180
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

The traditional tomato detection method of image segmentation is complex, and it is easy to be blocked by branches and leaves, fruit overlapping and other reasons, which affect the detection accuracy of fruit and the accurate positioning of picking points. This study proposes a fast identification and localization method of tomato based on YOLOv5 network. This method performs end-to-end detection by traversing the entire image with a single convolutional neural network, returning the class and location of the object. On the basis of YOLOv5, the regression box loss function is modified to improve the detection effect of tomato fruit, and the center point of the fruit boundary rectangle detected by YOLOv5 is used as the center point of tomato picking. The experimental results show that the average localization error of the proposed method is 1.379%, which is 1.867% lower than the traditional Hough method. The YOLOv5 method can effectively identify tomato fruits in natural environment. It can effectively detect tomatoes in overlapping, small targets, immature and other scenes, and perform more accurate positioning, laying a foundation for the tomato picking robot to select the best picking point.

Citation Download Citation

Chengyuan Song, Chao Wang, and Jian Song "Tomato identification and picking point location based on YOLOv5", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126103G (28 April 2023); https://doi.org/10.1117/12.2671180

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available