DocumentCode
2307713
Title
Definition of descriptors for semantic image interpretation
Author
Ivasic-Kos, Marina ; Poscic, Patrizia ; Pavlic, Mile
Author_Institution
Dept. for Comput. Sci., Univ. in Rijeka, Rijeka, Croatia
fYear
2010
fDate
5-6 July 2010
Firstpage
214
Lastpage
219
Abstract
A lot of effort has been put into researching image interpretation, but there is still no universally accepted approach to map low-level feature into high level image semantic interpretation. In this paper, a method for continuous low-level features vector quantization is presented so as to define appropriate values for descriptive variables. The similarity among different concepts of the domain is examined and compared by using the measure of similarity which is based on the probabilistic model and the measure of distance. Also, an abstract image description vector suitable for image analysis is given.
Keywords
content-based retrieval; feature extraction; image retrieval; probability; vector quantisation; abstract image description vector; content based image retrieval; descriptive variables; high level semantic image interpretation; image analysis; low-level feature vector quantization; probabilistic model; image classification; image representations; quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Information Processing (EUVIP), 2010 2nd European Workshop on
Conference_Location
Paris
Print_ISBN
978-1-4244-7288-8
Type
conf
DOI
10.1109/EUVIP.2010.5699133
Filename
5699133
Link To Document