Title
A flexible content-based image retrieval model and a customizable system for the retrieval of shapes
Abstract
The authors describe a flexible model and a system for content-based image retrieval of objects' shapes. Flexibility is intended as the possibility of customizing the system behavior to the user's needs and perceptions. This is achieved by allowing users to modify the retrieval function. The system implementing this model uses multiple representations to characterize some macroscopic characteristics of the objects shapes. Specifically, the shape indexes describe the global features of the object's contour (represented by the Fourier coefficients), the contour's irregularities (represented by the multifractal spectrum), and the presence of concavities and convexities (represented by the contour scale space distribution). During a query formulation, the user can specify both the preference for the macroscopic shape aspects that he or she considers meaningful for the retrieval, and the desired level of accuracy of the matching, which means that the visual query shape must be considered with a given tolerance in representing the desired shapes. The evaluation experiments showed that this system can be suited to different retrieval behaviors, and that, generally, the combination of the multiple shape representations increases both recall and precision with respect to the application of any single representation. © 2010 Wiley Periodicals, Inc.
Year
DOI
Venue
2010
10.1002/asi.v61:5
JASIST
Keywords
Field
DocType
flexible content-based image retrieval,contour scale space distribution,macroscopic shape aspect,visual query shape,different retrieval behavior,content-based image retrieval,system behavior,customizable system,flexible model,multiple shape representation,shape index,retrieval function,shape,customization,image retrieval
Computer vision,Information retrieval,Computer science,Adaptive system,Precision and recall,Image retrieval,Scale space,Fourier series,Artificial intelligence,Multifractal system,Content-based image retrieval,Visual Word
Journal
Volume
Issue
ISSN
61
5
1532-2882
Citations 
PageRank 
References 
5
0.38
33
Authors
2
Name
Order
Citations
PageRank
Gloria Bordogna1974103.99
Marco Pagani282.49