Affiliation:
1. College of Engineering, South China Agricultural University, Guangzhou 510070, China
2. Foshan-Zhongke Innovation Research Institute of Intelligent Agriculture and Robotics, Foshan 528200, China
Abstract
With the rapid development of the turtle breeding industry in China, the demand for automated turtle sorting is increasing. The automatic sorting of Chinese softshell turtles mainly consists of three parts: visual recognition, weight prediction, and individual sorting. This paper focuses on two aspects, i.e., visual recognition and weight prediction, and a novel method for the object detection and weight prediction of Chinese softshell turtles is proposed. In the individual sorting process, computer vision technology is used to estimate the weight of Chinese softshell turtles and classify them by weight. For the visual recognition of the body parts of Chinese softshell turtles, a color space model is proposed in this paper to separate the turtles from the background effectively. By applying multiple linear regression analysis for modeling, the relationship between the weight and morphological parameters of Chinese softshell turtles is obtained, which can be used to estimate the weight of turtles well. An improved deep learning object detection network is used to extract the features of the plastron and carapace of the Chinese softshell turtles, achieving excellent detection results. The mAP of the improved network reached 96.23%, which can meet the requirements for the accurate identification of the body parts of Chinese softshell turtles.
Funder
Dongguan wisdom aquaculture and unmanned processing equipment technology innovation platform
Reference34 articles.
1. Bureau, F. (2021). China Fishery Statistical Yearbook, China Agriculture Press.
2. Recent advances of machine vision technology in fish classification;Li;ICES J. Mar. Sci.,2022
3. Automated measurement of species and length of fish by computer vision;White;Fish. Res.,2006
4. Chen, S., Tang, Y., Zou, X., Huo, H., Hu, K., Hu, B., and Pan, Y. (2022). Identification and detection of biological information on tiny biological targets based on subtle differences. Machines, 10.
5. Dynamic visual servo control methods for continuous operation of a fruit harvesting robot working throughout an orchard;Chen;Comput. Electron. Agric.,2024