Improving the Shadow Compensation Using Fourier Analysis With Application to Face Recognition

• Main Authors: Shu-Mei Shiau, 蕭淑美
• Other Authors: Jan-Ray Liao
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/97111721178428051482

碩士 === 國立中興大學 === 通訊工程研究所 === 100 === Shadows that occur on face images due to illumination variation can change the appearance of a face and degrade face recognition performance. In this thesis, we implement and improve a new shadow compensation method based on the Fourier analysis for handling illumination variation. First, we classify the original images into three categories according to its illumination direction: (1) illumination from left, (2) uniform illumination, and (3) illumination from right. The classified images are then further classified into two sub-categories according to the area on the face that is covered by shadow: (1) 1/2 area and (2) 2/3 area. Second, after Fourier transform, we adjust the proportion between the auxiliary magnitude and the magnitude of the original image according to the classified category. The magnitude spectrum of the restored image is the sum of the auxiliary magnitude and the magnitude of the original image and its phase is the original phase components. The proposed method improved the shadow compensation as compared to the previous approach because of its adaptability on illumination direction. The experimental results and analysis show that the performance of our proposed method is indeed better than the original method significantly.