NDLI: Indexing wood image for retrieval based on kansei factors

Content Provider	IEEE Xplore Digital Library
Author	Fu Yali Cao Kui
Copyright Year	2008
Description	Author affiliation: Coll. of Comput. & Inf. Eng., Henan Univ., Kaifeng (Fu Yali; Cao Kui)
Abstract	According to the strong relationship between low level features in an image and human emotion, an approach to classify wood images into emotional categories(gorgeous vs. simple) is proposed in this paper. Through analyzing the wood texture feature by the viewpoint of visual perception and image analysis, some features are structured to depict the relationship between wood texture and human emotional feelings. And the method that extract the features which reflect the emotional changes of wood texture by calculating directionality and coarseness in Tamura texture quantity and coarseness by K-means cluster algorithm, and extracting the global color feature in HSV color space is proposed, and Back Propagation Neural Network is employed to map these low level features to emotional feature space. Finally, we show some experimental results.
Starting Page	1099
Ending Page	1102
File Size	240155
Page Count	4
File Format	PDF
ISBN	9781424421787
DOI	10.1109/ICOSP.2008.4697321
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indexing Image retrieval Humans Image texture analysis Image analysis Visual perception Image color analysis Feature extraction Clustering algorithms Neural networks
Content Type	Text
Resource Type	Article

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