Abstract
Plant classification is very important and necessary with respect to agricultural informization, ecological protection and plant automatic classification system. Compared with other methods, such as cell and molecule biology methods, classification based on leaf image is the first choice for plant classification. Plant recognition and classification is a complex and difficult problem, and is very important in Computer-Aided Plant Species Identification technology. The feature extraction is a key step to plant classification. This paper presents a method to extract discriminant features for plant leaf images by using supervised Isomap. Experiments on the leaf image dataset have been performed. Experimental results show that the supervised Isomap is very effective and feasible.
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Du, M., Zhang, S., Wang, H. (2009). Supervised Isomap for Plant Leaf Image Classification. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_67
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DOI: https://doi.org/10.1007/978-3-642-04020-7_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04019-1
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