In this paper we present a robust information integration approach to identifying images of persons in large collections, such as the web. The underlying system relies on combining content analysis, which involves face detection and recognition, with context analysis which involves extraction of text or HTML features. Two aspects are explored to test the robustness of this approach: Sensitivity...

This work is concerned with registration of data in geospatial databases, especially with registering images taken by different sensors and from different viewpoints of the same scene. This research has many applications in creating and updating maps, surveys and other geospatial data sources. While considerable work has been performed in image registration [2], extant approaches break down as ...

The general problem of object recognition is diicult and often requires a large amount of computing resources, even for locating an object within a single image. How, then, can it be possible to build a tool to for indexing into a a large database of, say, thousand of images, which works eeectively in \interactive time" on aaordable hardware? One important optimization is to take advantage of i...

We present here, an image description approach based on prosemantic features. The images are firstly represented by a set of low-level features related to their structure and color distribution. Those descriptions are fed to a battery of image classifiers trained to evaluate the membership of the images with respect to a set of 14 overlapping classes. Prosemantic features are obtained by packin...

Blobworld is a system for image retrieval based on finding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions (“blobs”) with associated color and texture descriptors. Querying is based on the attributes of one or two regions of interest, rather than a description of the entire image. In order to make large-scale retrieval feasible, we ...

As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from th...

Blobworld is a system for image retrieval based on nding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions (\blobs") with associated color and texture descriptors. Querying is based on the attributes of one or two regions of interest, rather than a description of the entire image. In order to make large-scale retrieval feasible, we in...

Traditional content based image indexing aims at developing algorithms that can analyze and index images based on their visual content. A typical approach is to measure image attributes, like colors or textures, and save the result in image descriptors, which then can be used in recognition and retrieval applications. Two topics within content based image indexing are addressed in this thesis: ...

Content-based indexing and query has been considered as a powerful technique for accessing large visual information systems (databases and video servers). By extracting and indexing the visual contents of the images such as texture, color, and shape, users may search desired images by specifying the image contents directly. However, a practical and economical solution cannot afford extensive us...