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Surface curvature based completed local ternary pattern for texture image classification
被引:0
|作者:
Chen, Xi
[1
]
Zhang, Yunfei
[1
]
Zhou, Zaihong
[2
]
机构:
[1] Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang 550025, Peoples R China
[2] Guangdong Med Univ, Sch Biomed Engn, Zhanjiang 524023, Guangdong, Peoples R China
基金:
中国国家自然科学基金;
关键词:
image curvature;
shape index;
completed local ternary pattern;
texture feature extraction;
ROTATION-INVARIANT;
FACE RECOGNITION;
RETRIEVAL;
GRADIENTS;
FEATURES;
SCALE;
COLOR;
D O I:
10.1504/IJBM.2023.133159
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
The curvature of two-dimensional function can describe the degree of surface curvature. When an image is treated as a discrete two-dimensional function, image curvature describes the structural relationship between local pixels of the image. Local ternary pattern is an effective image texture descriptor to encode shape index based on image curvature. In this paper, the completed local ternary pattern, which contains the symbol characteristics, amplitude characteristics and central pixel characteristics of the local ternary pattern of shape index (completed local ternary pattern based on shape index, SI-CLTP) are all considered at the same time. Experiments on two texture databases and one palmprint database fully show that shape index based completed local ternary pattern is an effective image texture descriptor.
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页码:606 / 622
页数:18
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