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Automate green coverage measure using a novel DIA method: UIP-MGMEP
By: Tao Lu; Wei Huang; Jianbo Hu; Xingyuan He; Wei Chen;
2011 / IEEE / 978-1-61284-848-8
This item was taken from the IEEE Conference ' Automate green coverage measure using a novel DIA method: UIP-MGMEP ' Green coverage is an important indicator of health status of rangeland, and it's meaningful to improve the efficiency, accuracy and objectivity of green coverage measurement. Digital image analysis (DIA) technique becomes more attractive; however, there have been few advances in automatic measurement methods. In this paper, we automate rangeland green coverage measure by DIA, which is a novel threshold segmentation algorithm named as UIP-MGMEP applied to the vegetation index (Excess Green (EXG) in this paper). UIP-MGMEP is not recommended to images whose fraction of vegetation is smaller than 0.5% or larger than 99.5%, which could be rounded to 0% or 100% visually. UIP-MGMEP optimizes EXG threshold by searching the upper inflexion point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of either background or vegetation is suppressed. The results show that UIP-MGMEP works well, and fails when either background or vegetation is too complex. UIP-MGMEP achieves accurate and objective green coverage measure without any human intervention. However, UIP-MGMEP is only developed to extract green-leaved vegetation, not suitable for non-green (even grayish-green) leaved vegetation. Accuracy could be improved through using VIS-NIR camera instead of VIS camera.
Green Coverage Measurement
Digital Image Analysis Technique
Threshold Segmentation Algorithm
Upper Inflexion Point
Green-leaved Vegetation Extraction
Image Edge Detection
Mean Gradient Magnitude
Image Colour Analysis
Rangeland Health Status Indicator