TY - GEN
T1 - Dimension reduction using semi-supervised locally linear embedding for plant leaf classification
AU - Zhang, Shanwen
AU - Chau, Kwok Wing
PY - 2009/11/11
Y1 - 2009/11/11
N2 - Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant species. Plant classification based on leaf images is a basic research of botanical area and agricultural production. Due to the high nature complexity and high dimensionality of leaf image data, dimensional reduction algorithms are useful and necessary for such type of data analysis, since it can facilitate fast classifying plants, and understanding and managing plant leaf features. Supervised locally linear embedding (SLLE) is a powerful feature extraction method, which can yield very promising recognition results when coupled with some simple classifiers. In this paper, a semi-SLLE is proposed and is applied to plant classification based on leaf images. The experiment results show that the proposed algorithm performs very well on leaf image data which exhibits a manifold structure.
AB - Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant species. Plant classification based on leaf images is a basic research of botanical area and agricultural production. Due to the high nature complexity and high dimensionality of leaf image data, dimensional reduction algorithms are useful and necessary for such type of data analysis, since it can facilitate fast classifying plants, and understanding and managing plant leaf features. Supervised locally linear embedding (SLLE) is a powerful feature extraction method, which can yield very promising recognition results when coupled with some simple classifiers. In this paper, a semi-SLLE is proposed and is applied to plant classification based on leaf images. The experiment results show that the proposed algorithm performs very well on leaf image data which exhibits a manifold structure.
KW - Locally linear embedding
KW - Plant classification
KW - Plant leaf image
KW - Semi-SLLE
KW - Supervised locally linear embedding (SLLE)
UR - http://www.scopus.com/inward/record.url?scp=70350776230&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04070-2_100
DO - 10.1007/978-3-642-04070-2_100
M3 - Conference article published in proceeding or book
SN - 3642040691
SN - 9783642040696
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 948
EP - 955
BT - Emerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings
T2 - 5th International Conference on Intelligent Computing, ICIC 2009
Y2 - 16 September 2009 through 19 September 2009
ER -
