A Green Vegetation Extraction Based-RGB Space in Natural Sunlight

Abstract:

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Green vegetation segmentation in color images is a fundamental issue for automated remote sensing and machine vision applications, plant ecological assessments, precision crop management, and weed control. A simple green vegetation feature extraction method (GVFE) is proposed in this paper to segment the green vegetation from their non-green backgrounds due to the fact that the green component content is always greater than that of the red and blue in RGB color space. The conventional based-auto-threshold method, ExG (Excess Green) was compared with GVFE, in which a green index ratio was defined to evaluate the performance of them. A digital color image set of single Canna flower taken in natural lighting were used to test them. Experimental results have showed that GVFE has superior performance over ExG+auto-threshold in term of stability, and is insensible to illuminant variations.

Info:

Periodical:

Advanced Materials Research (Volumes 225-226)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

660-665

DOI:

10.4028/www.scientific.net/AMR.225-226.660

Citation:

Z. B. Zhang et al., "A Green Vegetation Extraction Based-RGB Space in Natural Sunlight", Advanced Materials Research, Vols. 225-226, pp. 660-665, 2011

Online since:

April 2011

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Price:

$35.00

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