Face Illumination Compensation Based on Wavelet Transform

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Face Illumination Compensation Based on Wavelet Transform

Article | 更新时间：2020-08-12

- Face Illumination Compensation Based on Wavelet Transform
- Optics and Precision Engineering Vol. 16, Issue 1, Pages: 150-155(2008)
- 作者机构：
  
  1. 重庆三峡学院物理与电子工程学院
  2. 北京邮电大学模式识别实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：07 June 2007，
  
  Revised：27 July 2007，
  
  Published Online：22 January 2008，
  
  Published：22 January 2008
- 稿件说明：
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聂祥飞,谭泽富,郭军. 基于小波变换的人脸光照补偿[J]. 光学精密工程, 2008,16(1):150-155

Face Illumination Compensation Based on Wavelet Transform[J]. Optics and precision engineering, 2008, 16(1): 150-155.
聂祥飞,谭泽富,郭军. 基于小波变换的人脸光照补偿[J]. 光学精密工程, 2008,16(1):150-155 DOI：

Face Illumination Compensation Based on Wavelet Transform[J]. Optics and precision engineering, 2008, 16(1): 150-155. DOI：

摘要

提出了一种用于非均匀光照条件下人脸识别的光照补偿算法。该算法首先将人脸图像变换到对数域，并在对数域中计算2维小波变换，通过舍弃低频子带图像中的系数来实现人脸图像的非均匀光照补偿。由于人脸光照补偿的目的是为了提高人脸识别性能，所以光照补偿的效果利用人脸识别率来表征。在Yale B人脸库中，与对数域离散余弦变换（DCT）光照补偿算法进行了比较，实验结果表明，本文方法的人脸识别平均误识率可以达到0.18%，比对数域DCT方法具有更好的性能。另外，在CAS_PEAL人脸库中的实验结果表明，本文方法的性能与对数域DCT方法相近。

Abstract

A novel illumination compensation algorithm for face recognition under non-uniform illumination conditions was presented. Firstly

the face images were transformed from spatial domain to logarithm domain

and the 2-dimensional wavelet transform was calculated. Secondly

coefficients of low-frequency sub-band image were discarded for face illumination compensation in logarithm domain. The effect of face illumination compensation was denoted by face recognition rate because that the intention of illumination compensation was to improve the performance of face recognition. The proposed approach was compared with the discrete cosine transform (DCT) method in logarithm domain on Yale B face database. The experimental results show that the average error rate of the proposed approach can reach 0.18%

which is superior to the DCT method for face illumination compensation in logarithm domain. Additionally

the experimental results on CAS_PEAL face database indicate that the performance of the proposed algorithm is equivalent to the DCT method.

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