Region of Interest Based Image Retrieval with MATLAB Implementation

This article provides a comprehensive exploration of Region of Interest (ROI) based image retrieval technology, which utilizes computer vision techniques to identify and search for specific objects or regions within images. This methodology finds applications across various domains including medical image processing, security surveillance, and autonomous driving systems. In our implementation example, we employ MATLAB to demonstrate this technology, accompanied by practical code snippets and detailed explanations. The implementation typically involves key steps such as ROI detection using edge detection algorithms (e.g., Canny edge detector) or segmentation methods (like watershed algorithm), feature extraction using techniques such as SIFT or SURF descriptors, and similarity matching through distance metrics (Euclidean or Cosine distance). We provide working code examples that demonstrate how to use MATLAB's Image Processing Toolbox functions, including regionprops for region analysis and pdist2 for similarity calculations. The article aims to help readers better understand and apply this technology, particularly those interested in computer vision and image processing techniques. We hope this resource proves valuable for researchers and developers working on visual content analysis and retrieval systems.