Dimension reduction using semi-supervised locally linear embedding for plant leaf classification

Shanwen Zhang, Kwok Wing Chau

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

86 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationEmerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings
Pages948-955
Number of pages8
DOIs
Publication statusPublished - 11 Nov 2009
Event5th International Conference on Intelligent Computing, ICIC 2009 - Ulsan, Korea, Republic of
Duration: 16 Sep 200919 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5754 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Intelligent Computing, ICIC 2009
Country/TerritoryKorea, Republic of
CityUlsan
Period16/09/0919/09/09

Keywords

  • Locally linear embedding
  • Plant classification
  • Plant leaf image
  • Semi-SLLE
  • Supervised locally linear embedding (SLLE)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this