NDLI: Texture descriptor based on local combination adaptive ternary pattern

Content Provider	IET Digital Library
Author	Sandid, Faten Douik, Ali
Abstract	Material recognition has several applications, such as image retrieval, object recognition and robotic manipulation. To make the material classification more suitable for real-world applications, it is fundamental to satisfy two characteristics: robustness to scale and to pose variations. In this study, the authors propose a novel discriminant descriptor for texture classification based on a new operator called local combination adaptive ternary pattern (LCATP) descriptor used to encode both colour and local information. They start by building the LCATP descriptor using a combination of three different adaptive thresholding techniques. Moreover, they present a novel operator, mean histogram (MH), used jointly with the LCATP in order to incorporate colour information into the descriptor. This approach is then extended to four different colour spaces: LC 1 C 2, I 1 I 2 I 3, LSHuv and O 1 O 2 O 3. The final descriptor, LCATP fusion (LCATP_F), is produced by fusing the basic histogram (H) and MH extracted from the different colour spaces. Finally, the LCATP_F descriptor properties, such as the robustness to scale and pose changes are evaluated using the challenging KTH-textures under varying illumination, pose and scale (TIPS2b) dataset along with the least squares support vector machines classifier. The obtained experimental results, using the LCATP_F descriptor, show a significant improvement with respect to the state-of-the-art results.
Starting Page	634
Ending Page	642
Page Count	9
ISSN	17519659
Volume Number	9
e-ISSN	17519667
Issue Number	Issue 8, Aug (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/9/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2014.0895
Journal	IET Image Processing
Publisher Date	2015-08-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Thresholding Technique Colour Information Colour Space Computer Vision And Image Processing Technique Descriptor Property Image Colour Analysis Image Retrieval Image Segmentation Image Texture Information Retrieval Technique Interpolation And Function Approximation Knowledge Engineering Technique LCATP Descriptor Least Squares Approximation Least Squares Support Vector Machine Classifier Local Combination Adaptive Ternary Pattern Material Recognition Mean Histogram Novel Discriminant Descriptor Numerical Analysis Object Recognition Optical, Image And Video Signal Processing Pattern Classification Pose Variations Robotic Manipulation Support Vector Machine Texture Classification Texture Descriptor
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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