After two sets of images are captured by the system under different stages of plant growth and illumination conditions, each image is processed using algorithms provided by MATLAB from The MathWorks (Natick, MA, USA). Each RGB image is captured, then converted to a normalized excessive green (NEG) channel, represented by NEG = 2.8 ( g/r + g + b ) ( r/r + g + b ) ( b/r + g + b ) to emphasize the green channel. Before training, these images were pre-processed to measure specific morphological features of the plants within the images. After the plant perimeter, inner area, width, and height of a plant were measured, the features converted to five normalized featuresheight/width, height/perimeter, perimeter/area, width/area, and height/areato minimize the influences of the image size of each...[Read the full article]
söndag 9 oktober 2011
Vision-guided robot automates vegetation analysis
After two sets of images are captured by the system under different stages of plant growth and illumination conditions, each image is processed using algorithms provided by MATLAB from The MathWorks (Natick, MA, USA). Each RGB image is captured, then converted to a normalized excessive green (NEG) channel, represented by NEG = 2.8 ( g/r + g + b ) ( r/r + g + b ) ( b/r + g + b ) to emphasize the green channel. Before training, these images were pre-processed to measure specific morphological features of the plants within the images. After the plant perimeter, inner area, width, and height of a plant were measured, the features converted to five normalized featuresheight/width, height/perimeter, perimeter/area, width/area, and height/areato minimize the influences of the image size of each...[Read the full article]
