Introduction - If you have any usage issues, please Google them yourself
slic superpixelSLIC mainly uses the K-means clustering algorithm for ultra pixel processing, the distance measurement in the clustering algorithm includes not only the color distance of the color space, but also the Euclidean distance of the pixel coordinates. Therefore, the central point of K-means clustering consists of five dimensional vectors. These include the recording of pixels in the LAB color space, and the XY coordinates of the pixel points, so that a parameter of compactness is added because the XY coordinates cannot be directly computed with the color space.