Content-Based Image Retrieval Using Color Histograms

This MATLAB code performs content-based image retrieval using color histograms for image matching. The algorithm calculates similarity metrics to identify images in a database that are visually similar to a query image. The implementation follows these key steps: First, the input query image is converted into a color histogram representation, typically using RGB or HSV color space with appropriate binning. Second, all images in the database are preprocessed and converted into their corresponding color histogram representations. Third, the code computes similarity scores between the query image's histogram and each database image's histogram using distance metrics such as Euclidean distance, histogram intersection, or Chi-square distance. Finally, the system ranks the database images based on their similarity scores and returns the most similar matches. This implementation provides an efficient method for color-based image retrieval, allowing users to quickly find visually similar images in large databases through histogram comparison techniques.