Association based image retrieval: A survey

With advances in the computer technology and the World Wide Web there has been an explosion in the amount and complexity of multimedia data that are generated, stored, transmitted, analyzed, and accessed. In order to extract useful information from this huge amount of data, many content based image retrieval (CBIR) systems have been developed in the last decade. A typical CBIR system captures image features that represent image properties such as color, texture, or shape of objects in the query image and try to retrieve images from the database with similar features. Recent advances in CBIR systems include relevance feedback based interactive systems. In order to make the Image Retrieval more effective, Researchers are moving towards Association-Based Image Retrieval (ABIR) a new direction to CBIR. Image retrieval can be done effectively by associating the textual and visual clues of an image by reducing the semantic gap. This Survey paper focuses on the detailed review of different methods and their evaluation techniques used in the recent works based on ABIR systems. Finally, several recommendations for future research directions in ABIR have been suggested based on the recent technologies.