Content-based image retrieval

A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases. “Content-based” means that the search will analyze the actual content of the image. The term ‘content’ in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. Without the ability to examine image content, search must rely on metadata such as captions or keywords, which may be laborious or expensive to produce. How this problem is used in real world examples? Can algorithms really guess the similarity which is subjective category? Can similarity works without the context? How this reflects the consumer approach to online services? The presented paper gives some ideas that should clarify the raised questions.