Scalable integrated region-based image retrieval using IRM and statistical clustering
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Learning-based linguistic indexing of pictures with 2--d MHMMs
Proceedings of the tenth ACM international conference on Multimedia
Abstracting Visual Percepts to Learn Concepts
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
A Model-Based Approach to Semantic-Based Retrieval of Visual Information
SOFSEM '02 Proceedings of the 29th Conference on Current Trends in Theory and Practice of Informatics: Theory and Practice of Informatics
Towards Retrieval of Visual Information Based on the Semantic Models
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A real-time shot cut detector: Hardware implementation
Computer Standards & Interfaces
Atomic Vector Operations on Chip Multiprocessors
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
Accelerating Web Content Filtering by the Early Decision Algorithm
IEICE - Transactions on Information and Systems
Feature selection using genetic algorithm and cluster validation
Expert Systems with Applications: An International Journal
Semantic image segmentation with a multidimensional hidden markov model
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
| Hi-index | 0.00 |
From the Publisher:"Integrated Region-Based Image Retrieval, presents a wavelet-based approach for feature extraction, combined with integrated region matching. An image in the database, or a portion of an image, is represented by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. A measure for the overall similarity between images is developed as a region-matching scheme that integrates properties of all the regions in the images. The advantage of using this "soft matching" is that it makes the metric robust to poor segmentation, an important property that previous research has not solved. Integrated Region-Based Image Retrieval demonstrates an experimental image retrieval system called Simplicity (Semantics-sensitive Integrated Matching for Picture Libraries). This system validates these methods on various image databases, proving that such methods perform much better and much faster than existing ones. The system is exceptionally robust to image alterations such as intensity variation, sharpness variation, intentional distortions, cropping, shifting, and rotation. These features are extremely important to biomedical image databases since visual features in the query image are not exactly the same as the visual features in the images in the database." "Integrated Region-Based Image Retrieval is an excellent reference for researchers in the fields of image retrieval, multimedia, computer vision and image processing."--BOOK JACKET.