计算机科学 ›› 2009, Vol. 36 ›› Issue (8): 276-280.

• 图形图像及体系结构 • 上一篇    下一篇

基于改进型LBP特征的人脸识别方法研究

赵建民,朱信忠,江小辉   

  1. (浙江师范大学数理与信息工程学院 金华 321004)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(60772071),浙江省科技计划项目(2008C14063)资助。

Research on Face Recognition Technique Based on Improved LBP Features

ZHAO Jian-ming,ZHU Xin-zhong,JIANG Xiao-hui   

  • Online:2018-11-16 Published:2018-11-16

摘要: 不可控制条件是人脸识别应用到实际中的最重要瓶颈之一。寻求有效且分类性能高的人脸表征方法至关重要,在局部二值模式(LBP)的纹理提取基础上,引进一种改进的新型的局部三值模式(LTP)纹理特征提取方法,此方法对光照变化和噪声更加鲁棒且更有利于分类,最后采用PCA和Fisher线性判别分析对特征空间进行降维和最优鉴别分类。结合一系列简单实用的图像预处理方法,在JDL和AR两个标准人脸库上对此方法进行测试评价,实验结果表明此方法的有效性和可行性。

关键词: 纹理特征,Fisher线性判别,局部三值模式,滤波

Abstract: Recognition in uncontrolled situations is one of the most bottlenecks for practical face recognition. It is crucial to seek a valid and power discriminant method for facial appearance. Based on the local binary patterns for extract local texture, introducing a improved-new method called local ternary patterns, which is more rubost and more power discriminant for illumination variations and noise. Finally, PCA and Fisher linear discriminant arc used to reduce the dimensionalily and optimize discriminative classification respectively. Combing a simple and efficient image preprocessing chain,The mothod is tested and evaluated not only on JDL datasets but also AR datasets, promising results presented the method is valid and feasible.

Key words: Texture extract,Fisher linear discriminant,Local ternary patterns,Filter

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