NDLI: Scene image classification: Some novel descriptors

Content Provider	IEEE Xplore Digital Library
Author	Banerji, S. Sinha, A. Chengjun Liu
Copyright Year	2012
Description	Author affiliation: New Jersey Institute of Technology, Newark, 07102, USA (Banerji, S.; Sinha, A.; Chengjun Liu)
Abstract	This paper introduces several novel color, shape and texture-based image descriptors for scene image classification with applications to image search and retrieval. Specifically, first, a new 3-Dimensional Local Binary Pattern (3DLBP) descriptor is proposed for color image local feature extraction. Second, a new shape descriptor (HaarHOG) is introduced by combining Haar wavelet transformation and Histogram of Oriented Gradients (HOG). Third, these descriptors are fused using an optimal feature representation technique to generate a robust 3-Dimensional LBP-HaarHOG (3DLH) descriptor that can perform well on different scene image categories. Finally, the Enhanced Fisher Model (EFM) is applied for discriminatory feature extraction and the nearest neighbor classification rule is used for image classification. The proposed descriptors and fusion technique are evaluated using three grand challenge datasets: the MIT Scene dataset, the UIUC Sports Event dataset, and a part of the Caltech 256 dataset.
Starting Page	2294
Ending Page	2299
File Size	1257988
Page Count	6
File Format	PDF
ISBN	9781467317139
e-ISBN	9781467317146
e-ISBN	9781467317122
DOI	10.1109/ICSMC.2012.6378083
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-14
Publisher Place	Korea (South)
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis Feature extraction Vectors Color Principal component analysis Gray-scale Wavelet transforms scene classification The HaarHOG descriptor the 3-Dimensional Local Binary Pattern (3D-LBP) descriptor the 3DLH descriptor Enhanced Fisher Model (EFM) image search
Content Type	Text
Resource Type	Article

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