A Novel Adaptively Binarizing Magnitude Vector Method in Local Binary Pattern Based Framework for Texture Classification-Reference-Cited by-同舟云学术

A Novel Adaptively Binarizing Magnitude Vector Method in Local Binary Pattern Based Framework for Texture Classification

Published:2022 Issue: Volume:29 Page:852-856
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Hu Shiqi¹,Pan Zhibin²^ORCID,Dong Jing³,Ren Xincheng⁴

Affiliation:

1. Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China

2. Faculty of Electronic and Information Engineering and the Research Institute of Zhejiang Province, Xi’an Jiaotong University, Xi’an, China

3. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

4. School of Physics and Electronic Information and the Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data, Yanan University, Yanan, China

Funder

National Natural Science Foundation of China

Key Science and Technology Program of Shaanxi Province

Open Project of Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data

Zhejiang Provincial Commonweal Project

National Laboratory of Pattern Recognition

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/97/9686799/09732688.pdf?arnumber=9732688

Reference25 articles.

1. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

2. A completed modeling of local binary pattern operator for texture classification;guo;IEEE Trans Image Process,2010

3. Feature based local binary pattern for rotation invariant texture classification

4. Completed Local Binary Count for Rotation Invariant Texture Classification

5. Adaptive center pixel selection strategy in Local Binary Pattern for texture classification

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