Plant species identification based on modified local discriminant projection
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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.
KeywordsPlant species identification Maximum margin criterion (MMC) Local discriminant projection (LDP) Modified LDP (MLDP)
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.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.
- 6.Chaki J, Parekh R (2011) Plant leaf recognition using shape based features and neural network classifiers. Int J Adv Comput Sci Appl 2(10):41–47Google Scholar
- 9.Lu C, Feng J, Lin Z et al (2018) Subspace clustering by block diagonal representation. IEEE Trans Pattern Anal Mach Intell 99:1–11Google Scholar
- 10.Yang LW, Wang XF (2012) Leaf image recognition using Fourier transform based on ordered sequence. Intell Comput Technol Lect Notes Comput Sci 7389:393–400Google Scholar
- 13.Yan S, Xu D, Zhang B, Zhang H-J (2005) Graph embedding: a general framework for dimensionality reduction. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 830–837Google Scholar
- 15.Chen HT, Chang HW, Liu TL (2005) Local discriminant embedding and its variants. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 846–853Google Scholar
- 19.Shanwen Z, Xianfeng W, Zhen W et al (2015) Probability locality preserving discriminant projections for plant recognition. Trans Chin Soc Agric Eng (Trans CSAE) 31(11):215–220 (in Chinese with English abstract) Google Scholar