VIRMA: visual image retrieval by shape MAtching

Authors:
G. Castellano;C. Castiello;A. M. Fanelli
Affiliations:
Computer Science Department, University of Bari, Bari, Italy;Computer Science Department, University of Bari, Bari, Italy;Computer Science Department, University of Bari, Bari, Italy
Venue:
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Year:
2006

Citing 6
Cited 0

An Efficiently Computable Metric for Comparing Polygonal Shapes

IEEE Transactions on Pattern Analysis and Machine Intelligence
Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Image Retrieval by Elastic Matching of User Sketches

IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond query by example

MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Shape Similarity Measure Based on Correspondence of Visual Parts

IEEE Transactions on Pattern Analysis and Machine Intelligence
Retrieval by shape similarity with perceptual distance andeffective indexing

IEEE Transactions on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

The huge amount of image collections connected to multimedia applications has brought forth several approaches to content-based image retrieval, that means retrieving images based on their visual content instead of textual descriptions. In this paper, we present a system, called VIRMA (Visual Image Retrieval by Shape MAtching), which combines different techniques from Computer Vision to perform content-based image retrieval based on shape matching. The architecture of the VIRMA system is portrayed and algorithms underpinning the developed prototype are briefly described. Application of VIRMA to a database of real-world pictorial images shows its effectiveness in visual image retrieval.