Color and texture have long been used as image features to segment and classify images. In most of the previous approaches, color and texture are used as two uncorrelated features, while in the real world, the spatial information and spectral information of an image are often tightly coupled. An feature extraction algorithm is studied in this paper, which represents colored texture in a unified way. With this approach, different spectral channels are correlated spatially to give an unified representation of both the color and texture information. In order to use this feature in image segmentation applications, properties of the feature are studied. A novel segmentation algorithm is proposed based on the study. Preliminary segmentation results are presented.