Recognition of leaf image set based on manifold-manifold distance
Ji-Xiang Du1; Mei-Wen Shao1; Chuan-Min Zhai1; Jing Wang1; Yuanyan Tang2; Chun Lung Philip Chen2
Source PublicationNeurocomputing

Recognizing plant leaves has been a difficult and important work. In this paper, we formulate the problems by classifying leaf image sets rather than single-shot image, each of set contains leaf images pertaining to the same class. We extract leaf image feature and compute the distance between two manifolds modeled by leaf images. Specifically, we apply a clustering procedure in order to express a manifold by a collection of local linear models. Then the distance is measured between local models which come from different manifolds that constructed above. Finally, the problem is transformed to integrate the distance between pairs of subspace. Experiment based on the leaves (ICL) from intelligent computing laboratory of Chinese academy of sciences, which shows that the method has a great performance.

KeywordLeaf Image Set Manifold-manifold Distance Phog Descriptor Plant Leaves Classification
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000375170000015
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Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorJi-Xiang Du
Affiliation1.Department of Computer Science and Technology, Huaqiao University, Xiamen, China
2.Faculty of Science and Technology, University of Macau, Macau, China
Recommended Citation
GB/T 7714
Ji-Xiang Du,Mei-Wen Shao,Chuan-Min Zhai,et al. Recognition of leaf image set based on manifold-manifold distance[J]. Neurocomputing,2016,188:131-138.
APA Ji-Xiang Du,Mei-Wen Shao,Chuan-Min Zhai,Jing Wang,Yuanyan Tang,&Chun Lung Philip Chen.(2016).Recognition of leaf image set based on manifold-manifold distance.Neurocomputing,188,131-138.
MLA Ji-Xiang Du,et al."Recognition of leaf image set based on manifold-manifold distance".Neurocomputing 188(2016):131-138.
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