Image similarity search is a technique that enables the retrieval of visually similar images from a large database based on a query image. Unlike traditional image search methods that rely on metadata like tags or descriptions, image similarity search uses computer vision techniques to compare the actual content of images. This is typically done by converting images into vector representations using deep learning models, such as convolutional neural networks (CNNs), and comparing their distance in a high-dimensional space.
Applications include reverse image search (like Google Images), product recommendation in e-commerce (finding similar products), and identifying duplicate or near-identical images in digital libraries. Image similarity search is useful for a variety of industries, including retail, digital media, and security.