Sharif Digital Repository

Nowadays the number of digital images has largely increased because of progress in internet technology. Management of this volume of data needs an efficient system for browsing, categorizing, and searching the images. The goal of this research is to design a system for automatic annotation of unobserved images for better search in image data bases. Automatic image annotation is a multi-label classification problem with many labels which suggests some words for describing the content of an image. Designing AIA systems faces chanllenges like semantic gap between low level image features and high level human expressions (tags), incompelete tags and imbalance images per tags in the datasets.... 

Automatic image annotation is an image retrieval mechanism to extract relative semantic tags from visual contents. The number of digital images uploaded in the virtual world is rapidly growing every day. Most of those images are not assigned with proper tags or labels. Although automatic image annotation methods are developed to assign proper tags to images, most of these methods assign some irrelevant tags and also sometimes a few relevant tags are missing. So far, the improvements of accuracy in newly developed automatic image annotation methods have been about one or two percent in F1-score compared to the previous methods. To reach much better performance, we analyzed most of the...