Abstract
The Plant recognition 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 recognition algorithms using plant leaf images are not enough for practical application. A modified maximum margin criterion (MMMC) algorithm is proposed for plant recognition by minimizing the within-class scatter, while maximizing the between-class scatter. The experimental results on the ICL leaf image database show that the proposed method is effective.
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References
Wang, X.F., Huang, D.S., Du, J.X., et al.: Classification of plant leaf images with complicated background. Appl. Math. Comput. 205(2), 916–926 (2008)
Huang, D.S., Du, J.X.: A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks. IEEE Trans. Neural Networks 19(12), 2099–2115 (2008)
Du, J.X., Zhai, C.M., Wang, Q.P.: Recognition of plant leaf image based on fractal dimension feature. Neurocomputing 116, 150–156 (2013)
Zhang, S.W., Lei, Y.K., Dong, T.B., et al.: Label propagation based supervised locality projection analysis for plant leaf classification. Pattern Recogn. 46(7), 1891–1897 (2013)
Wang, X.F., Huang, D.S.: A novel density-based clustering framework by using level set method. IEEE Trans. Knowl. Data Eng. 21(11), 1515–1531 (2009)
Chaki, J., Parekh, R.: Plant leaf recognition using shape based features and neural network classifiers. Int. J. Adv. Comput. Sci. Appl. 2(10), 41–47 (2011)
Chaki, J., Parekh, R., Bhattacharya, S.: Plant leaf recognition using texture and shape features with neural classifiers. Pattern Recogn. Lett. 58(1), 61–68 (2015)
Munisami, T., Ramsurmn, S.K., Sameerch, P., et al.: Plant leaf recognition using shape features and colour histogram with K-nearest neighbor classifiers. Procedia Comput. Sci. 58, 740–747 (2015)
Bama, B.S., Valli, S.M., Raju, S., et al.: Content based leaf image retrieval using shape, color and texture features. Indian J. Comput. Sci. Eng. 2(2), 202–211 (2011)
Yang, L.W., Wang, X.F.: Leaf image recognition using fourier transform based on ordered sequence. In: Huang, D.S., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds.) ICIC 2012. LNCS, vol. 7389, pp. 393–400. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31588-6_51
Zhang, S.W., Lei, Y.K.: Modified locally linear discriminant embedding for plant leaf recognition. Neurocomputing 74, 2284–2290 (2011)
Zhang, S.W., Lei, Y.K., Wu, Y.H.: Semi-supervised locally discriminant projection for recognition. Knowl. Based Syst. 24, 341–346 (2011)
Xu, S.Y., Zhang, B., Zhang, H.J.: Graph embedding: a general framework for dimensionality reduction. In: Proceedings of. IEEE Conference on Computer Vision and Pattern Recognition, pp. 830–837 (2005)
Yan, S., Xu, D., Zhang, B., Zhang, H.J.: Graph embedding and extensions: a general framework for dimensionality reduction. IEEE Trans. Pattern Anal. Mach. Intell. 29(1), 40–51 (2007)
Chen, H.T., Chang, H.W., Liu, T.L.: Local discriminant embedding and its variants. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 846–853 (2005)
Li, H., Jiang T., Zhang K.: Efficient and robust feature extraction by maximum margin criterion. In: Advances in Neural Information Processing Systems, pp. 97–104 (2003)
Li, H., Jiang, T., Zhang, K.: Efficient and robust feature extraction by maximum margin criterion. IEEE Trans. Neural Networks 17, 157–165 (2006)
Belhumeur, V., Hespanha, J., Kriegman, D.: Eigenfaces vs Fisher faces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–720 (1997)
Zhang, S.W., Wang, X.F., Wang, Z., et al.: Probability locality preserving discriminant projections for plant recognition. Trans. Chin. Soc. Agric. Eng. (Transactions of the CSAE) 31(11), 215–220 (2015). (in Chinese with English abstract)
Li, B., Wang, C., Huang, D.S.: Supervised feature extraction based on orthogonal discriminant projection. Neurocomputing 73, 191–196 (2009)
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Wang, X., Zhang, S., Wang, Z. (2018). Plant Recognition Based on Modified Maximum Margin Criterion. In: Huang, DS., Gromiha, M., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science(), vol 10956. Springer, Cham. https://doi.org/10.1007/978-3-319-95957-3_54
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DOI: https://doi.org/10.1007/978-3-319-95957-3_54
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