Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A texture thesaurus for browsing large aerial photographs
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Understanding intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Empirical evaluation of dissimilarity measures for color and texture
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Features in Content-based Image Retrieval Systems: a Survey
State-of-the-Art in Content-Based Image and Video Retrieval [Dagstuhl Seminar, 5-10 December 1999]
Toward Perception-Based Image Retrieval
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Modeling adaptive autonomous agents
Artificial Life
Automatic image segmentation by integrating color-edge extraction and seeded region growing
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Efficient and possibly intelligent image retrieval is an important task, often required in many fields of human activity. While traditional database indexing techniques exhibit a remarkable performance in textual information retrieval current research in content-based image retrieval is focused on developing novel techniques that are biologically motivated and efficient. It is well known that humans have a remarkable ability to process visual information and to handle the volume and complexity of such information quite efficiently. In this paper, we present a content-based image retrieval platform that is based on a multi-agent architecture. Each agent is responsible for assessing the similarity of the query image to each candidate image contained in a collection based on a specific primitive feature and a corresponding similarity criterion. The outputs of various agents are integrated using one of several voting schemes supported by the system. The system's performance has been evaluated using various collections of images, as well as images obtained in specific application domains such as medical imaging. The initial evaluation has yielded very promising results.