Accurate recognition method of plant leaves based on multi-feature fusion

Ruikai Lin; Junwei Ma; Huiling Yu; Yizhuo Zhang

doi:10.1117/12.2611757

22 October 2021 Accurate recognition method of plant leaves based on multi-feature fusion

Ruikai Lin, Junwei Ma, Huiling Yu, Yizhuo Zhang

Proceedings Volume 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021); 119280Q (2021) https://doi.org/10.1117/12.2611757
Event: International Conference on Image Processing and Intelligent Control (IPIC 2021), 2021, Lanzhou, China

Abstract

During the use of a convolutional neural network to train a recognition model of plant leaves, the convolutional layers focus on the appearance of leaves in learning the features of them, while ignoring their internal texture features, thereby resulting in the misclassification of plant leaves with similar appearance. Aiming at this problem, this paper proposes an accurate identification method of plant leaves based on multi-feature fusion, which can be applied to extract the appearance and texture features of leaves simultaneously, and to conduct fusion and summation for these two types of features. The experimental results indicate that compared with the accuracy of the ordinary convolutional neural network recognition method and traditional machine learning method, the accuracy of this method has been improved substantially.

Citation Download Citation

Ruikai Lin, Junwei Ma, Huiling Yu, and Yizhuo Zhang "Accurate recognition method of plant leaves based on multi-feature fusion", Proc. SPIE 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021), 119280Q (22 October 2021); https://doi.org/10.1117/12.2611757

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KEYWORDS

Convolutional neural networks

Data modeling

Image classification

Performance modeling

Detection and tracking algorithms

Feature extraction

Neural networks

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