A Human Face Classification Approach on Local Color Binary Patterns

TANG Xi-xi; LIANG Peng; WO Yan; JIA Xi-ping

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A Human Face Classification Approach on Local Color Binary Patterns

更新时间：2026-09-04

- A Human Face Classification Approach on Local Color Binary Patterns
- Vol. 30, Issue 3, Pages: 38-42(2013)
- 作者机构：
  
  1. 1 广西工学院计算机学院,广西,柳州,545006
  2. 2 广东技术师范学院机构计算机科学学院,广东,广州,510665
  3. 3 华南理工大学计算机科学与工程学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：
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- Published：2013
- 稿件说明：
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唐西西, 梁鹏, 沃焱, 贾西平. 基于局部彩色二元模式纹理特征的人脸分类方法[J]. 微电子学与计算机, 2013, 30(3): 38-42.

TANG Xi-xi, LIANG Peng, WO Yan, et al. A Human Face Classification Approach on Local Color Binary Patterns[J]. 2013, 30(3): 38-42.
唐西西, 梁鹏, 沃焱, 贾西平. 基于局部彩色二元模式纹理特征的人脸分类方法[J]. 微电子学与计算机, 2013, 30(3): 38-42. DOI：

TANG Xi-xi, LIANG Peng, WO Yan, et al. A Human Face Classification Approach on Local Color Binary Patterns[J]. 2013, 30(3): 38-42. DOI：

摘要

针对现有的局部纹理特征在光照变化下的人脸分类准确率不高的问题

提出一种局部彩色二元模式纹理特征提取和表示方法.该方法首先求取多个信号通道的彩色向量的模

以减少单独对每个信号通道提取LBP特征导致的量化误差;其次提取任意两个信号通道之间的像素彩色夹角来减少光照变化的影响.对于给定的测试人脸图像集

通过SVM的二分类器投票得到人脸图像的分类.在Color FERET和XM2VTSDB人脸图像数据库上的实验证明该方法在光照变化下可以有效地分类人脸图像.

Abstract

Aiming at low classification rate of local texture features for illumination human face classification

this paper proposed a local color binary patterns method for texture feature extraction and presentation.We first compute the norm of color vector between multi-channels to reduce quantify errors caused by extracting LBP features from each channel individually.Then

we extract the pixel color angular between each two channels to reduce illumination influence.Given test human face image dataset

the face is classified by SVM.The experimental results on standard dataset Color FERET and XM2VTSDB demonstrate the effectiveness of our method.

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