The ever-increasing interest in digital image retrieval has led to research into ways of reducing and if possible eliminating the cost of traditional image annotation. This report describes the development of an automatic image annotation and contentbased image retrieval system. The process documented in this paper has an initial training phase in which the associations between words and images...

Multi-level annotation of images is a promising solution to enable semantic image retrieval by using various keywords at different semantic levels. In this paper, we propose a multi-level approach to interpret and annotate the semantics of natural images by using both the dominant image components and the relevant semantic image concepts. In contrast to the well-known image-based and region-bas...

Due to the large amounts of multimedia data prevalent on the Web, Some images presents textural motifs while others may be recognized with colors or shapes of their content. The use of descriptors based on one’s features extraction method, such as color or texture or shape, for automatic image annotation are not efficient in some situations or in absence of the chosen type. The proposed approac...

Automatic Image Annotation (AIA) is an effective technology to improve the performance of images retrieval from large image collections by text queries. In this paper, we propose a novel AIA scheme based on finding the most similar images using a distance metric and then transferring the annotation to the query image. The proposed method can effectively deal with the problem of finding the resu...