This paper studies Latent Semantic Analysis (LSA) between visual and textual elements of a multimedia collection, applied on two different tasks: (1) multimedia document retrieval (MDR) and (2) automatic image annotation (AIA). Latent semantics, usually used for text indexing, is applied to discover hidden semantic relations between visual and textual descriptors. The contributions of this pape...

In this position paper we examine the limitation of region growing segmentation techniques to extract semantically meaningful objects from an image. We propose a region growing algorithm that performs on a semantic level, driven by the knowledge of what each region represents at every iteration step of the merging process. This approach utilizes simultaneous segmentation and labeling of regions...

The aim of the project Meta-Image, funded by German Research Foundation (DFG), is to provide a network-based research environment for art history and other sciences concerning visual culture. It consists of the two components prometheus and HyperImage. Meta-Image combines the distributed digital image archive prometheus, which consists of a very large pool of images, with HyperImage (http://www...

In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based measure – de-symmetrised mutual information (DTMI). We then describe a straightforward solution to the annotation problem. We first train a set of classifiers to detect the presence of each individ...

The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications in the automatic generation of structured radiology reports. Much of the prior research work has focused on annotating images with properties such a...

In this paper we report results of experiments conducted with strategies for improving text-based image retrieval. The adopted strategies were evaluated in the photographic retrieval task at ImageCLEF2007. We propose a Webbased method for expanding textual queries with related terms. This technique was the top-ranked query expansion method among those proposed by other ImageCLEF2007 participant...

Semantic annotation attaches to various concepts (e.g. people, things, places, organizations etc) in any other content. A semantically annotated document is easy to interpret, combine and reuse by computers. In human history Web plays as the greatest information source. Many researchers believe semantic annotations can be inserted in web-based documents for information extraction and knowledge ...

Automatic annotation of medical images is an increasingly important tool for physicians in their daily activity. Hospitals produce nowadays an increasing amount of data. Manual annotation is very costly and prone to human mistakes. This paper proposes a multi-cue approach to automatic medical image annotation. We represent images using global and local features. These cues are then combined tog...

The popularity of online social media has provided a huge repository of multimedia contents. To effectively retrieve and store this multimedia content and to mine useful pattern from this data is a herculean task. This paper deals with the problems of social image tagging. Multimedia tagging i.e. assigning tags or some keywords to multimedia contents like images, audio, video etc. by users is r...

Automatic annotation can automatically annotate images with semantic labels to significantly facilitate image retrieval and organization. Traditional web image annotation methods often estimate specific label relevance to image, and neglect the relevance of the assigned label set as a whole. In this paper, A novel image annotation method by heuristic relevance learning is proposed. Label releva...