Color images include three-valued information of each pixel and measure the intensity and chrominance of the light. Before applying segmentation to the color image, it should be made precise. The proposed method identifies plant disease by processing the plant leaf image [3]. The leaf of the plant constitutes veins and disease spots with a different color. A leaf is converted to a greyscale image and then segmentation is applied to locate vein and disease spots. However, we are concerned about the disease spots not the veins [4]. To reduce vein presence, RGB component is color transformed before segmentation. Using the following three techniques color image processing is performed:
- YCbCr color model is the most popular color space. In this model, Y represents luminance component, and Cb and Cr represent chrominance. It is widely used in video and image compression.
- HSI color model is a tool used for developing an algorithm in image processing based on color. In HSI model, H denotes hue, which describes pure color; S denotes saturation, which describes how much pure color is mixed with white; and I stands for intensity measuring brightness.
- CIELAB color model is defined as color space. It can be represented by mathematical operations to express the range of colors. Typically, there are three to four values of color components. It is used for display purpose and also for printing.
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