Automatic text processing
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Evaluating a content based image retrieval system
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Automated binary texture feature sets for image retrieval
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
In recent years, there has been an explosion in the use of digital photographic images in computers, especially since digital image creation facilities such as digital cameras, scanners, etc., are becoming increasingly popular. This development in digital photography has led to a huge collection of still images that are stored in digital format. As the demand for digital images increases, the need to store and retrieve images in an efficient manner arises. Therefore, the field of content-based image retrieval has emerged as an important research area in computer vision and image processing. The key issue in image retrieval is how to match two images according to computationally extracted features. Since speed and accuracy are important, we need to develop a system for retrieving images that is both efficient and effective. In this paper, we analyse one such content-based image retrieval system and test its suitability for building medical image databases.