Leaf vein extraction using independent component analysis

Yan Li, Zheru Chi, David D. Feng

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

Abstract

The purpose of this work is to develop an interactive tool which helps botanists to extract the vein system with its hierarchical properties with as little user interaction as possible. In this paper, we present a new venation extraction method using independent component analysis (ICA). The popular and efficient FastICA algorithm is applied to patches of leaf images to learn a set of linear basis functions or features for the images and then the basis functions are used as the pattern map for vein extraction. In our experiments, the training sets are randomly generated from different leaf images. Experimental results demonstrate that ICA is a promising technique for extracting leaf veins and edges of objects. ICA, therefore, can play an important role in automatically identifying living plants.
Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
Pages3890-3894
Number of pages5
Volume5
DOIs
Publication statusPublished - 28 Aug 2007
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan
Duration: 8 Oct 200611 Oct 2006

Conference

Conference2006 IEEE International Conference on Systems, Man and Cybernetics
CountryTaiwan
CityTaipei
Period8/10/0611/10/06

ASJC Scopus subject areas

  • Engineering(all)

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