Image retrieval using multi-scale color clustering
Sehwan Kim, Woontack Woo, Yo‐Sung Ho · 2002
A fundamental issue in content-based image retrieval is how to select image features that can represent image contents appropriately. A multi-scale color clustering algorithm based on human perceptual properties of color images is proposed for image retrieval. The multi-scale clustering algorithm is an unsupervised clustering method that utilizes the perceptual uniformity property in the (p,q) color space. The proposed color clustering algorithm produces a small set of representative color vectors for each image that capture color properties of the image, and a set of correlogram values that contain the spatial information of the image.