In this paper, an automatic image annotation and retrieval model is developed base on the intensity invariant approach. The given uncaptioned image is divided into background and foreground images and segmented into regions, which are classified into region types using a variety of features. Firstly, preprocessing stages such as gray-scale converting, noise filtering for image enhancing is proc...

In this paper, the automatic annotation task of the 2005 CLEF cross-language image retrieval campaign (ImageCLEF) is described. This paper focuses on the database used, the task setup, and the plans for further medical image annotation tasks in the context of ImageCLEF. Furthermore, a short summary of the results of 2005 is given. The automatic annotation task was added to ImageCLEF in 2005 and...

Automatic image annotation provides means for users to search image collections on the semantic level using natural language queries. In the past, statistical machine translation models have been successfully applied to automatic image annotation. A problem with this approach is that, due to the skewed distribution of term frequency for annotation words, common words have been overly favored, w...

Title of Dissertation: IMAGE MANAGEMENT USING PATTERN RECOGNITION SYSTEMS Bongwon Suh, Doctor of Philosophy, 2005 Dissertation Directed By: Associate Professor Benjamin B. Bederson, Department of Computer Science With the popular usage of personal image devices and the continued increase of computing power, casual users need to handle a large number of images on computers. Image management is c...

Title of Dissertation: IMAGE MANAGEMENT USING PATTERN RECOGNITION SYSTEMS Bongwon Suh, Doctor of Philosophy, 2005 Dissertation Directed By: Associate Professor Benjamin B. Bederson, Department of Computer Science With the popular usage of personal image devices and the continued increase of computing power, casual users need to handle a large number of images on computers. Image management is c...

Automatic image annotation has been becoming an attractive research subject. Most current image annotation methods are based on training techniques. The major weaknesses of such solutions include limited annotation vocabulary and labor-intensive involvement. However, Web images possess a lot of texts, and rich annotation of samples is provided. Therefore, this report provides a novel image anno...

Automatic image annotation techniques are proposed for overcoming the so-called semantic-gap between image low-level feature and high-level concept in content-based image retrieval systems. Due to the limitations of techniques, current state-of-the-art automatic image annotation models still produce some irrelevant concepts to image semantics, which are an obstacle to getting high-quality image...

Image segmentation and Automatic Image Annotation (AIA) are two important areas that still impose challenging problems. Addressing both problems simultaneously may improve their results since they are interdependent. In this paper we give a step ahead in that direction considering different segmentation levels simultaneously and possible contextual relations among segments in order to improve t...