With the advancement of Image acquisition and storing, image retrieval has been proven as the research problem. Many approaches for image retrieval, has been stated by researchers to solve the image retrieval problem. In this paper we state DFT transform based approach for image retrieval using Image classes. Here formation of Feature vectors of the Images is based on Color based DFT Phase information of images those belongs to same class. DFT Image transform provides effective way to differentiate the image textures. Particularly Phase part of DFT carries the important information about the objects in image. In the proposed approach of image retrieval, DFT phase information is used for representing the images using feature vector effectively. To make image retrieval more accurate, class wise images are considered for creation of database feature vectors. As, images belonging same class are content wise similar, the generalized feature vector is produced for each class Generalized feature vectors represents all images of that class. Cosine correlation similarity measure is used in the proposed approach. 4 Different types of feature vectors are created and tested for each image class. The Images are retrieved based on the feature vector values of DFT Phase information of RGB's planes with similar to that of Feature vector of Image class. Image retrieval Performance of the proposed approach is compared for database of 1000 images of 10 different categories. Average Accuracy of Image retrieval is above 60% for all classes and more than 75% for some of the image classes. © 2017 IEEE.