GLCMs

Gray Level Co-occurrence Matrices, often abbreviated as GLCMs, are a statistical method used in image analysis to explore the spatial relationship of pixels within an image. They quantify the second-order statistics of an image by measuring how often pairs of gray levels occur in specific spatial relationships. A GLCM is essentially a matrix where each entry represents the frequency of a particular pair of gray levels occurring at a specified distance and orientation from each other.

The construction of a GLCM involves defining a kernel or offset, which specifies the relative positions of the two pixels being considered. For instance, an offset of (1,0) would examine horizontally adjacent pixels. The matrix is populated by iterating through the image and incrementing the appropriate cell based on the gray levels of the pixel pair and their defined spatial relationship. The resulting matrix captures information about texture, contrast, homogeneity, and other visual characteristics that are not evident from examining individual pixel values alone.

GLCMs are widely employed in various image processing applications, including texture analysis, image segmentation, and object recognition. By analyzing the features extracted from a GLCM, such as contrast, correlation, energy, and homogeneity, it is possible to differentiate between different textures and classify image regions. This makes GLCMs a valuable tool in fields such as medical imaging, remote sensing, and computer vision.