Automatic Image Annotation using Image Clustering in Multi – Agent Society

The rapid growth of the internet provides tremendous resource for information in different domains (text, image, voice, and many others). This growth introduces new challenge to hit an exact match due to huge number of document returned by search engines where millions of items can be returned for certain subject. Images have been important resources for information, and billions of images are searched to fulfill user demands, which face the mentioned challenge. Automatic image annotation is a promising methodology for image retrieval. However most current annotation models are not yet sophisticated enough to produce high quality annotations. This thesis presents online intelligent indexing for image repositories based on their contents, although content based indexing and retrieving systems have been introduced, this thesis is adding an intelligent technique to re-index images upon better understanding for its composed concepts. Collaborative Agent scheme has been developed to promote objects of an image to concepts and re-index it according to domain specifications. Also this thesis presents automatic annotation system based on the interaction between intelligent agents. Agent interaction is synonym to socialization behavior dominating Agent society. The presented system is exploiting knowledge evolution revenue due to the socialization to charge up the annotation process

How to annotate an image? The need of an image annotation guide agent

[[abstract]]The performance of retrieving an image in terms of text-type of queries depends heavily on the quality of the annotated descriptive metadata that describes the content of the images. However, effective annotation of an image can often be a laborious task that requires consistent domain knowledge. We showed that the critical property and common sense heuristics used by an annotation guide agent to aid the annotation of images could significantly lead to the improvement of the recall and precision of image retrieval.[[fileno]]2030212030014[[department]]資訊工程學