Separating pigment components of leaf color image using FastICA

Authors:
Yuan Tian;Chunjiang Zhao;Shenglian Lu;Xinyu Guo
Affiliations:
Department of Automation, University of Science and Techonology of China, Hefei, Anhui, P.R. China and National Engineering Research Center for Information Technology in Agriculture, Beijing, P.R. ...;Department of Automation, University of Science and Techonology of China, Hefei, Anhui, P.R. China;Department of Automation, University of Science and Techonology of China, Hefei, Anhui, P.R. China;Department of Automation, University of Science and Techonology of China, Hefei, Anhui, P.R. China
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

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Abstract

In this paper, the spatial distributions of pigments in foliage which lead to color variation are separated by independent component analysis (ICA) from a single leaf color image. The results can be applied to the reproduction of leaf color, the diagnosis of leaf disease, and leaf texture synthesis. Our results shows that the components of pigments which are different color influential factor are separated from leaf color image. We use images to demonstrate results and show how each component of pigment affects the leaf color.