Paper Info
Title
A human-oriented image retrieval system using interactive genetic algorithm
Abstract
Content-based image retrieval has been actively studied in several fields. This provides more effective management and retrieval of images than the keyword-based approach. However, most of the conventional methods lack the capability to effectively incorporate human intuition and emotion into retrieving images. It is difficult to obtain satisfactory results when the user wants the image that cannot be explicitly described or can be requested only based on impression. In order to solve this problem and supplement the lack of the user's expression capability, we have developed an image retrieval system based on human preference and emotion by using an interactive genetic algorithm (IGA). This system extracts the feature from images by wavelet transform, and provides a user-friendly means to retrieve an image from a large database when the user cannot clearly define what the image must be. Therefore, this facilitates the search for the image not only with explicit queries, but also with implicit queries such as "cheerful impression," "gloomy impression," and so on. A thorough experiment with a 2000 image database shows the usefulness of the proposed system.
Year
DOI
Venue
2002
10.1109/TSMCA.2002.802812
IEEE Transactions on Systems, Man, and Cybernetics, Part A
Keywords
Field
DocType
retrieving image,cheerful impression,human preference,gloomy impression,implicit queries,explicit queries,content-based image retrieval,interactive genetic algorithm,image retrieval,human-oriented image retrieval system,proposed system,genetic algorithms,wavelet transform,interactive systems,image database,expression capability,human intuition,image retrieval system,content-based retrieval,information retrieval,wavelet transforms,feature extraction,indexing terms
Computer vision,Human–computer information retrieval,Automatic image annotation,Information retrieval,Feature detection (computer vision),Impression,Computer science,Image retrieval,Artificial intelligence,Genetic algorithm,Visual Word,Wavelet transform
Journal
Volume
Issue
ISSN
32
3
1083-4427
Citations 
PageRank 
References 
42
2.27
8
Authors
2
Name
Order
Citations
PageRank
Sung-Bae Cho12875265.52
Joo-Young Lee27712.36