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Plant species identification based on modified local discriminant projection

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Abstract

Plant species identification based on plant leaves is important for biological science, ecological science, and agricultural digitization. Because of the complexity and variation of the plant leaves, many classical plant species identification algorithms using plant leaf images are not enough for practical application. A modified local discriminant projection (MLDP) algorithm is proposed for plant species identification. MLDP aims to extract discriminant features for plant species identification by taking class label information into account based on the property of locality preserving. The MLDP can preserve the local geometrical structure of leaves and extract the strong discriminative ability. The experimental results on the public ICL leaf image database show the effectiveness and feasibleness of the proposed method.

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Acknowledgements

This work was supported by the Grants of the National Science Foundation of China (No. 61473237). It is also supported by the basic research project of natural science in Shaanxi Province under Grant Nos. 2017ZDXM-NY-088, 2016GY-141.

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Authors and Affiliations

  1. Department of Information Engineering, Xijing University, Xi’an, 710123, China

    Shanwen Zhang, Wenzhun Huang & Zhen Wang

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  1. Shanwen Zhang
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  2. Wenzhun Huang
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  3. Zhen Wang
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Correspondence to Shanwen Zhang.

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Zhang, S., Huang, W. & Wang, Z. Plant species identification based on modified local discriminant projection. Neural Comput & Applic 32, 16329–16336 (2020). https://doi.org/10.1007/s00521-018-3746-0

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  • DOI: https://doi.org/10.1007/s00521-018-3746-0

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