IMAGE RETRIEVAL BASED ON DISCRETE CURVELET TRANSFORM

Abstract

Content-Based Image Retrieval (CBIR) is a process of searching for an image according to the content or feature that is within it. Nowadays, most image retrieval applications have been developed to meet these needs, so this application will provide comfort in introducing and searching for an image. This paper proposed a standard structured framework with three stages: Preprocessing is the first step, in which noise from images is removed using various filters. The filters' results are compared to determine the best and most appropriate filter for the images. Feature Extraction of images using Curvelet Transform is the second stage. The third stage includes similarity measurement between query image features to database image features and extracting the identical image from the image dataset. The system was performed using Matlab 2017b, GUI and, with ten different classes of 1000 images using a coral database. The results show improved performance of precision and recall when higher decomposition levels are used.