Using color image processing techniques to improve the performance of content-based image retrieval systems

A Content-Based Image Retrieval (CBIR) system is a mechanism intended to retrieve a particular image from a large image repository without resorting to any additional information about the image. Query-by-example (QBE) is a technique used by CBIR systems where an image is retrieved from the database based on an example given by the user. The effectiveness of a CBIR system can be measured by two main indicators: how close the retrieved results are to the desired image and how fast we got those results.;In this thesis, we implement some classical image processing operations in order to improve the average rank of the desired image, and we also implement two object recognition techniques to improve the subjective quality of the best ranked images. Results of experiments show that the proposed system outperforms an equivalent CBIR system in QBE mode, both from the point of view of precision as well as recall.