Content-based image Retrieval techniques can be divided into two main domains: pixel and compressed domain techniques. In the pixel domain, the values of individual pixels in the image matrix are used directly for making visual indexes. In the compressed domain, transformed data, which is the result of mapping the original image matrix into another domain, is employed for feature extraction and retrieval. One of the main tasks for Content-based image Retrieval (CBIR) systems is similarity comparison, extracting feature of every image based on its pixel values and defining rules for comparing images. These features become the image representation for measuring similarity with other images in the database. Images are compared by calculating the difference of its feature components to other image descriptors i.e namely colour, texture and shape features. In this article we are going to discuss the color descriptors. Grid Color Movement Colour feature is one of the most widely used features in low level feature. Associated with shape feature, Colour feature and texture feature shows better stability and is more insensitive to the rotation and zoom of the image. Colour not only adds beauty to objects but also more information that is used as a powerful tool in content-based image retrieval….