Color image edge detection using cluster analysis
A color image edge detection algorithm is proposed based on the idea that use global color information to guide local gradient computation. The major chromatic components of an image are first extracted through cluster analysis. According to these color clusters, a set of linear chromatic transforms are generated. An appropriate chromatic transform is chosen for each pixel to maximize the gradient magnitude. In this way, edges are treated as transitions from one cluster to another. The algorithm is implemented and experimental results for real color images are included.