DocumentCode
1539278
Title
SIMPLIcity: semantics-sensitive integrated matching for picture libraries
Author
Wang, James Z. ; Li, Jia ; Wiederhold, Gio
Author_Institution
Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA
Volume
23
Issue
9
fYear
2001
fDate
9/1/2001 12:00:00 AM
Firstpage
947
Lastpage
963
Abstract
We present here SIMPLIcity (semantics-sensitive integrated matching for picture libraries), an image retrieval system, which uses semantics classification methods, a wavelet-based approach for feature extraction, and integrated region matching based upon image segmentation. An image is represented by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. The system classifies images into semantic categories. Potentially, the categorization enhances retrieval by permitting semantically-adaptive searching methods and narrowing down the searching range in a database. A measure for the overall similarity between images is developed using a region-matching scheme that integrates properties of all the regions in the images. The application of SIMPLIcity to several databases has demonstrated that our system performs significantly better and faster than existing ones. The system is fairly robust to image alterations
Keywords
content-based retrieval; feature extraction; image classification; image retrieval; image segmentation; pattern clustering; pattern matching; visual databases; wavelet transforms; SIMPLIcity; clustering; content based image retrieval; feature extraction; image segmentation; region matching; semantics classification; visual databases; wavelet; Content based retrieval; Image classification; Image databases; Image retrieval; Image segmentation; Image storage; Information retrieval; Libraries; Pixel; Robustness;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.955109
Filename
955109
Link To Document