NDLI: Multiple features-based image retrieval

Content Provider	IEEE Xplore Digital Library
Author	Yanyan Gao Honggang Zhang Jun Guo
Copyright Year	2011
Description	Author affiliation: Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, China (Yanyan Gao; Honggang Zhang; Jun Guo)
Abstract	Color and texture information are two important visual features of an image. In this paper, an efficient content-based image retrieval system is proposed based on color and texture feature. The color feature is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by color histogram. Texture feature is obtained by local binary pattern (LBP). When computing the similarity between query image and target images in the database, Gaussian normalization is exploited on the feature space and distant space. And then the linear combination of normalized distances for color and texture is performed to obtain the similarity as the index of image. The exhaustive search scheme is used for retrieval, and the evaluation criterion is precision and recall about the number of returned images. The results of experiments demonstrate the efficiency of the proposed system.
Starting Page	240
Ending Page	244
File Size	163180
Page Count	5
File Format	PDF
ISBN	9781612841588
e-ISBN	9781612841595
DOI	10.1109/ICBNMT.2011.6155933
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Visualization Image color analysis Image retrieval Multi-feature Feature extraction Vectors Texture feature Content-based image retrieval Color feature
Content Type	Text
Resource Type	Article

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