Tag relevance fusion for social image retrieval

Tag Relevance for Social Image Retrieval in Accordance with Neighbor Voting Algorithm

Social image retrieval is important for exploiting the increasing amounts of amateur-tagged multimedia such as Flickr images. Intuitively, if different persons label similar images using the same tags, these tags are likely to reflect objective aspects of the visual content. Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging proble...

Document Image Retrieval Based on Keyword Spotting Using Relevance Feedback

Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...

Tag-based social image retrieval: An empirical evaluation

Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order o...

Image Fusion For Medical Image Retrieval

Kernel Indexmg for Relevance Feedback Image Retrieval

Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index structure in order to reduce nearest neighbor computation. However, flexible metrics can alter an input space in a highly nonlinear fashion, thereby rendering the index structure useless. Few systems have been developed that...