Abstract
AbstractAn automatic image annotation approach is proposed to bridge the semantic gap issues in image retrieval. It begins with building connection between semantic concept and image region by image segmentation, and then extracting visual features from image region in order to find the correlativity between semantic concept and image region in the annotated image while annotation, calculating the similarities between different image regions to annotate the unannotated target images, using the given correlativity as a priori knowledge. Experiments conducted on a 2000 image dataset demonstrate the effectiveness and efficiency of the proposed approach for image annotation.KeywordsSemantic ConceptImage RegionVisual FeaturesPriori Knowledgeimage retrieval
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
