A novel adaptive two-stage selection strategy in local binary pattern for texture classification-Reference-Cited by-同舟云学术

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A novel adaptive two-stage selection strategy in local binary pattern for texture classification

Published:2023-07-24 Issue:8 Volume:17 Page:4039-4048
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Hu Shiqi,Li Jie,Fan Hongcheng,Lan Shaokun,Pan Zhibin

Funder

the National Natural Science Foundation of China

the Key Science and Technology Program of Shaanxi Province

the Zhejiang Provincial Commonweal Project

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02634-8.pdf

Reference28 articles.

1. Zhao, X., Xue, L., Xu, F.: Asphalt pavement paving segregation detection method using more efficiency and quality texture features extract algorithm. Constr. Build. Mater. 277, 122302 (2021)

2. Duan, M., Zhang, X.: Using remote sensing to identify soil types based on multiscale image texture features. Comput. Electron. Agric. 187, 106272 (2021)

3. Florindo, J.B., Metze, K.: A cellular automata approach to local patterns for texture recognition. Expert Syst. Appl. 179, 115027 (2021)

4. Yang, C.: Plant leaf recognition by integrating shape and texture features. Pattern Recognit. 112, 107809 (2021)

5. Zhang, J., Liang, J., Zhang, C., Zhao, H.: Scale invariant texture representation based on frequency decomposition and gradient orientation. Pattern Recognit. Lett. 51, 57–62 (2015)

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