Algorithm for acquiring lettuce plant height based on image recognition network

Xiyue Guo; Yong Zhong; Ming Zhao; Man Zhang; Minjuan Wang

doi:10.1117/12.2684683

19 October 2023 Algorithm for acquiring lettuce plant height based on image recognition network

Xiyue Guo, Yong Zhong, Ming Zhao, Man Zhang, Minjuan Wang

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127090D (2023) https://doi.org/10.1117/12.2684683
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Lettuce height is one of the important phenotypic parameters of lettuce. Currently, evaluating plant height information based on RGB images is the most convenient and fastest method. However, these tasks often require complex camera calibration operations or reference objects with known heights, which are somewhat limiting. Therefore, we utilize a deep neural network to solve this problem to directly obtain the height of lettuce from RGB images without camera calibration and reference objects. This paper integrates four high-performance image recognition networks MobileNetV1, Densenet-121, ResNext-50, and EfficientNet-B3 using average fusion and linear fusion methods to predict lettuce plant height. Experiments show that we have achieved good results, the accuracy of the four basic models has been improved, and the average absolute error has been reduced to varying degrees. The smallest reduction is Efficient-Net, which has decreased 0.01 mm, the largest drop is the ResNext-50, which is 0.15 mm lower. After the model is averagely fused, the average absolute error is further reduced to 1.22 mm, and the maximum absolute error is reduced to 6.48 mm, which is not only better than linear. The fusion results are better than the prediction results of a single model.

Citation Download Citation

Xiyue Guo, Yong Zhong, Ming Zhao, Man Zhang, and Minjuan Wang "Algorithm for acquiring lettuce plant height based on image recognition network", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127090D (19 October 2023); https://doi.org/10.1117/12.2684683

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KEYWORDS

Machine learning

Deep learning

Data modeling

Feature extraction

Education and training

RGB color model

Cameras

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