Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Querying multimedia data from multiple repositories by content: the Garlic project
Proceedings of the third IFIP WG2.6 working conference on Visual database systems 3 (VDB-3)
Matching 2D polygonal arcs by using a subgroup of the unit quaternions
Computer Vision and Image Understanding
Data Warehousing in the Real World: A Practical Guide for Building Decision Support Systems
Data Warehousing in the Real World: A Practical Guide for Building Decision Support Systems
Visually Searching the Web for Content
IEEE MultiMedia
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cognitive informatics models of the brain
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Invariant matching and identification of curves using B-splines curve representation
IEEE Transactions on Image Processing
Large-Scale geospatial indexing for image-based retrieval and analysis
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
| Hi-index | 0.00 |
This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing. It also provides an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features. Experimental results confirm that the new approach is feasible for content-based image retrieval.