ARTICLE HISTORY: Received 01 January 2016 Revised 12 June 2016 Accepted 13 June 2016 With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of the most challenging fields in image processing. Automatic image annotation (AIA) or refers to attachi...

Automatic image annotation is an important tool for keyword-based image retrieval, providing a textual index for non-annotated images. Many image auto annotation methods are based on visual similarity between images to be annotated and images in a training corpus. The annotations of the most similar training images are transferred to the image to be annotated. In this paper we consider using al...

Automatic image annotation (AIA) is an active topic of research in computer vision and pattern recognition. In the last two decades, large amount of researches on AIA have been proposed, mainly including classification-based methods and probabilistic modeling methods. As one of the most common methods for AIA, support vector machine (SVM) has been widely applied in the multimedia research commu...

In this paper, a novel automatic image annotation system is proposed, which integrates two sets of support vector machines (SVMs), namely the multiple instance learning (MIL)-based and global-feature-based SVMs, for annotation. The MIL-based bag features are obtained by applying MIL on the image blocks, where the enhanced diversity density (DD) algorithm and a faster searching algorithm are app...

We researched and developed a practical methodology for face and image retrieval (FIR) based on optimally weighted image descriptor ensemble. We describe a single-image-per-person (SIPP) face image retrieval system for real-world applications that include large photo collection search, person location in disaster scenarios, semi-automatic image data annotation, etc. Our system provides efficien...

Automatic image annotation is a promising solution to enable the semantic image retrieval via keywords. In this paper, we present a robust probabilistic latent semantic analysis (PLSA) for the task of automatic image annotation. On the one hand, since labeled images are often hard to obtain or create in large quantities while the unlabeled ones are easier to collect. Semi-supervised learning ai...

This paper presents our techniques used and their analysis for the runs made and the results submitted by the CINDI group for the task of the image retrieval and automatic annotation of ImageCLEF 2006. For the ah-hoc image retrieval from both the photographic and medical image collections, we have experimented with cross-modal (image and text) interaction and integration approaches based on the...

Annotation of MEDLINE citations with controlled vocabulary terms improves the quality of retrieval results. Due to variety in descriptions of similar clinical phenomena and abundance of negation and uncertainty, annotation of clinical radiology reports for subsequent indexing and retrieval with a search engine is even more important. Provided with an opportunity to add about 4,000 radiology rep...