LETRIST : locally encoded transform feature histogram for rotation-invariant texture classification

LETRIST : locally encoded transform feature histogram for rotation-invariant texture classification

Classifying texture images, especially those with significant rotation, illumination, scale, and viewpoint changes, is a fundamental and challenging problem in computer vision. This paper proposes a simple yet effective image descriptor, called Locally Encoded TRansform feature hISTogram (LETRIST),...

Полное описание

Библиографические подробности
Главные авторы: Song, Tiecheng, Li, Hongliang, Meng, Fanman, Wu, Qingbo, Cai, Jianfei
Другие авторы: School of Computer Science and Engineering
Формат: Journal Article
Язык:English
Опубликовано: 2020
Предметы:
Engineering::Electrical and electronic engineering
Texture Classification
Texture Analysis
Online-ссылка:https://hdl.handle.net/10356/142172

Internet

https://hdl.handle.net/10356/142172

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