Visual retrieval by content in an Image DataBase (IDB) is still an open problem. So far, various methods with different semantic levels have been developed, for internet search or off-line IDBs, but few of them take into account the user's perceptual point of view. Two features primarily used for visual retrieval in IDBs are shape and color. We focus our attention on color, from the perspective of color appearance. The Human Visual System (HVS) has adaptation mechanisms that cause the user to perceive the relative chromaticity of an area, rather than its absolute color. In addition, due to the acquisition process, color distortions are added to heterogeneous IDBs. Digital pictures of real objects for IDBs must be digitized and the acquisition process is composed of various passages and means, each one introducing unwanted color shifting. Moreover, the color quantization and the device gamut can introduce additional distortion on the original color information. The overall result is a recognizable and the device gamut can introduce additional distortion on the original color information. The overall result is a digital image that can significantly differ in color from the real object. For the user the image may still be easily recognizable, but the color search change can vary widely and differ for each image or for the same image with different acquisition processes. For this reason, the user's perceptual point of view must be added into the management of color. The idea presented in this paper adds a pre-filtering algorithm that simulates the HVS and that discounts the acquisition color distortion in the query image as well as in each image in the IDB. Moreover, we suggest to use for the image retrieve, a more perceptively linear chromatic distance in the color comparison.