DocumentCode :
2863124
Title :
Semantic Tolerance Relation-Based Image Representation and Classification
Author :
Dai, Ying
Author_Institution :
Iwate Pref. Univ., Iwate
fYear :
2007
fDate :
11-13 Oct. 2007
Firstpage :
62
Lastpage :
67
Abstract :
The nature of the concepts regarding images in many domains are imprecise, and the interpretation of finding similar images is also ambiguous and subjective on the level of human perception. To solve these problems, in this paper, images´ semantic categories and the tolerance degree between them are defined systematically, and the approach of modeling tolerance relations between the semantic classes is proposed. Furthermore, for removing the induced false tolerance in the produce of using semantic tolerance relation model, the method of un- tolerating is introduced in image representation. We apply the proposed approach to the representations of images regarding the nature vs. man-made domain, human vs. non-human domain, and temporal domain, and compare the categorization results of them with the results not using semantic tolerance relation model. The results show the effectiveness of proposed method.
Keywords :
image classification; image representation; image classification; image representation; semantic tolerance relation; Database languages; Feedback; Humans; Image analysis; Image color analysis; Image databases; Image representation; Image retrieval; Pervasive computing; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Pervasive Computing, 2007. IPC. The 2007 International Conference on
Conference_Location :
Jeju City
Print_ISBN :
978-0-7695-3006-2
Type :
conf
DOI :
10.1109/IPC.2007.26
Filename :
4438395
Link To Document :
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