MATLAB Implementation of Content-Based Image Retrieval with Query Point Learning Algorithm

This documentation presents a MATLAB-based content-based image retrieval (CBIR) system designed for relevance feedback retrieval. The system implements our proprietary query point learning algorithm (with published research papers) that employs machine learning techniques to automatically learn optimal query points from input datasets. The algorithm's core implementation involves feature extraction using color histograms and texture descriptors, followed by a relevance feedback mechanism where users mark relevant/irrelevant images to refine search results. Key MATLAB functions include imread() for image preprocessing, pdist2() for similarity measurement, and custom optimization functions for query point updating. We believe this algorithm shows significant potential in image retrieval applications, enabling users to locate target information more efficiently. Furthermore, we are continuously exploring algorithm optimizations through dimensionality reduction techniques and kernel methods to enhance system performance and accuracy, with the goal of achieving improved results in future iterations.