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Research on target detection and recognition algorithm of Eriocheir sinensis carapace

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Abstract

Chinese mitten crab is one of China's unique aquaculture species, which has significant economic value to the aquatic product market. In order to recognize different individual Chinese mitten crab, this paper proposes a method of first detection and recognition of carapace combined with YOLOv5 (You Only Look Once v5) and principal component analysis (PCA) and its improved method. First, the image of the Chinese mitten crab is obtained through the camera. Secondly, YOLOv5 and transfer learning method are used to detect the target of the Chinese mitten crab, and then the target is automatic cropped according to the detected target frame of Chinese mitten crab carapace. Finally, four methods of KPCA, one-dimensional PCA (1D-PCA), two-dimensional PCA (2D-PCA), and two-way two-dimensional PCA ((2D)2-PCA) were used for matching. The results show that the (2D)2-PCA recognition rate can reach 84.42%, which is 18.27%, 9.128% and 8.689% higher than the other three methods respectively. In addition, the matching speed only takes 1.859 s, compared with the other three methods. The method improves by 86.051 s, 2.562 s and 0.784 s, respectively. Therefore, this method has a better experimental effect in the experiment, and the recognition speed is faster. The results of the study can avoid the economic loss of aquatic products and provide a new research method for the recognition of the Chinese mitten crab carapace.

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Data availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Chinese mitten crab samples in this article were provided by Sihong Youziwei Ecological Agricultural Products Co., Ltd. The photos of the crab pond breeding of Hongze Lake crabs are provided by Manager Tianyu Ling. Wang Wei, Laboratory of Genetics, Breeding and Biotechnology, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, and Jianbo Dong, Jiangsu Fishery Law Enforcement and Supervision Center, gave guidance to the biological content of hairy crabs in the article.

Funding

This work was supported by National Natural Science Foundation of China under Grant No. 61936014, Laoshan Laboratory under Grant No.LSKJ202201804, Chinese Academy of Fishery Sciences basic scientific research fees under Grant No. 2020TD82.

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Author notes

  1. Jiaze Zhang and Shuxian Wang contributed equally to the research in this paper.

Authors and Affiliations

  1. Key Laboratory of Fisheries Remote Sensing, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China

    Jiaze Zhang, Shuxian Wang, Shengmao Zhang, Jiakang Li & Yueying Sun

  2. College of Information, Shanghai Ocean University, Shanghai, China

    Jiaze Zhang, Jiakang Li & Yueying Sun

  3. School of Navigation and Naval Architecture, Dalian Ocean University, Dalian, China

    Shuxian Wang

  4. Laoshan Laboratory , Qingdao, China

    Shengmao Zhang

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  1. Jiaze Zhang
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  2. Shuxian Wang
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  4. Jiakang Li
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  5. Yueying Sun
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Correspondence to Shengmao Zhang.

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Zhang, J., Wang, S., Zhang, S. et al. Research on target detection and recognition algorithm of Eriocheir sinensis carapace. Multimed Tools Appl 82, 42527–42543 (2023). https://doi.org/10.1007/s11042-023-15228-w

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  • DOI: https://doi.org/10.1007/s11042-023-15228-w

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