色调
色度
RGB颜色模型
人工智能
计算机视觉
数学
反射率
天蓬
遥感
植物
地理
计算机科学
生物
光学
物理
作者
Irfan Ahmad,John F. Reid
标识
DOI:10.1006/jaer.1996.0020
摘要
The object of the study was to evaluate the use of colour image information to characterize stress levels owing to water and nitrogen deficiencies in maize leaves and variations in colour due to normal physiological growth of plants. A machine vision system was used to collect Red, Green and Blue (RGB) colour features interactively from slide images of the maize plants. Hue, saturation and intensity (HSI) and red, green and blue (r, g, b) chromaticity coordinate transformations of the data were also evaluated. Colour calibration standards placed in each image revealed minor colour variability. The major changes in the appearance of plants occurred for living leaf tissue. The senescent crop canopy leaf area changed with increased nitrogen levels, but colour representation data did not show any visible trends in colour changes. The evaluation of various colour representations revealed that colour variations in maize plant images were distinctly detectable using HSI as compared with RGB and chromaticity coordinates. Colour provided a classifying feature with which particular plant and leaf colour was recognized.
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