Title
Using Fuzzy DLs to Enhance Semantic Image Analysis
Abstract
Research in image analysis has reached a point where detectors can be learned in a generic fashion for a significant number of conceptual entities. The obtained performance however exhibits versatile behaviour, reflecting implications over the training set selection, similarities in visual manifestations of distinct conceptual entities, and appearance variations of the conceptual entities. In this paper, we investigate the use of formal semantics in order to benefit from the logical associations between the conceptual entities, and thereby alleviate part of the challenges involved in extracting semantic descriptions. More specifically, a fuzzy DL based reasoning framework is proposed for the extraction of enhanced image descriptions based on an initial set of graded annotations, generated through generic image analysis techniques. Under the proposed reasoning framework, the initial descriptions are integrated and further enriched at a semantic level, while additionally inconsistencies emanating from conflicting descriptions are resolved. Experimentation in the domain of outdoor images has shown very promising results, demonstrating the added value in terms of accuracy and completeness of the resulting content descriptions.
Year
DOI
Venue
2008
10.1007/978-3-540-92235-3_5
SAMT
Keywords
Field
DocType
distinct conceptual entity,generic fashion,conceptual entity,outdoor image,enhance semantic image analysis,enhanced image description,initial set,proposed reasoning framework,initial description,fuzzy dls,generic image analysis technique,image analysis,formal semantics
Training set,Data mining,Information retrieval,Computer science,Fuzzy logic,Description logic,Added value,Visual Manifestations,Completeness (statistics),Semantics of logic,Conceptual Entity
Conference
Volume
ISSN
Citations 
5392
0302-9743
11
PageRank 
References 
Authors
0.49
18
3
Name
Order
Citations
PageRank
S. Dasiopoulou127718.37
Ioannis Kompatsiaris21404197.36
Michael Gerasimos Strintzis31171104.83