1. First, we read the angiolipoma tissue images entered in the software.
2. We display three main colors in the image: background color, purple, and magenta. The color space L * a * b * (also known as CIELAB or CIE L * a * b *) minimizes these visual differences. The color space L * a * b * is derived from the values of tristimulus CIE XYZ. The space L * a * b * consists of a layer of luminosity "L *" or a layer of light, the color layer "a *" which indicates the placement of the color along the red-green axis, and the colored layer "b *" which indicates the placement of the color in the extension is composed. The approach is to select a small sample area for each color and calculate the average color of each sample area in the space 'a * b *'. We use these color markers to classify each pixel.
3. Classify Each Pixel Using the Nearest Neighbor Rule.
4. Display Results of Nearest Neighbor Classification.
One of the statistical methods for examining texture that considers the spatial relationship of pixels is the gray surface event matrix (GLCM), also known as the gray surface spatial dependence matrix. GLCM functions determine the texture of an image by calculating the number of times a pair of pixels of a certain value occurs in a given spatial relationship in an image, generate a GLCM, and then extract statistical metrics from this matrix.
After creating GLCM, several statistics can be extracted from them using the graycoprops function. This statistic provides information about the texture of an image. The table below shows the statistics.