•  
  •  
 

International Journal of Image Processing and Vision Science

Abstract

The performance of most existing face recognition methods is highly sensitive to illumination variation. It will be seriously degraded if the training/testing faces under variable lighting. Thus, illumination variation is one of the most significant factor affecting the performance of face recognition and has received much attention in recent years. In this paper we propose a novel method called gradientface for face recognition under varying illumination. When we rarely know the strength, direction or number of light sources. The proposed method has the ability to extract illumination insensitive measure, which is then used for face recognition. The merits of this method is that neither does it require any lighting assumption nor does it need any training images. Gradientface method reaches very high recognition rate of 98.96% in the test on yele B face database. Further more the experimental results on Yale database validate that gradient faces is also insensitive to image noise and object artifacts such as facia;l expression.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.