The quick response content based image retrieval (QR-CBIR) systems using hybrid features descriptor are utilized to discover the matching images in comparison to the query image. The CBIR models are designed by using the combination of the feature descriptor with classification algorithm, where the feature descriptor is used for deriving the visual or texture based features from the training and testing images, which is followed by the phase distance or probability based classification algorithm. In this paper, the hybrid feature descriptor has been proposed by combining the color and texture based feature descriptors, which are aimed to achieve the quick response feature descriptor model. The proposed model is aimed at resolving the issue of quick response CBIR models for the big image database querying. The performance of the proposed model will be estimated using the precision, recall and accuracy factors.
Color and texture feature descriptors, Support Vector Machine (SVM), CBIR, Quick Response CBIR (QR-CBIR).