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標題: 改善傅立葉分析在人臉識別上做陰影補償的應用
Improving the Shadow Compensation Using Fourier Analysis With Application to Face Recognition
作者: 蕭淑美
Shiau, Shu-Mei
Contributors: 廖俊睿
Jan-Ray Liao
通訊工程研究所
關鍵字: 人臉識別;傅立葉轉換;照明變化;光照方向;陰影補償
Face recognition;Fourier transforms;illumination variation;illumination direction;shadow compensation
日期: 2012
Issue Date: 2013-11-19 12:31:30 (UTC+8)
Publisher: 通訊工程研究所
摘要: 由於光照的變化,使得人臉產生陰影,改變了臉部的外觀,並且降低臉部識別的特性。因此,我們提出一個新的陰影補償方式,是以傅立葉分析為基礎來處理光照對於改變人臉辨識度的影響。而我們採用改良由傅立葉分析在人臉識別上做陰影補償的方式。
首先,我們提出先將原始影像根據光照的方向進行分類:光線從左邊照射、均勻照射和右邊照射,再依照人臉上陰影覆蓋區域的多寡做第二次分類:1/2與2/3區域被陰影遮蓋。在傅立葉轉換後,藉由將原始影像的幅度與輔助的頻譜幅度作一個比例的相加,再和原先保留的相位結合,來重建被陰影所惡化的人臉圖像。而每一個類別都有各自一組輔助頻譜幅度與影像原本幅度的相加比例,並依照類別使用不同相加比例,作為補償陰影的方式。
在光照的變動之下,由於不同的光照方向與人臉上被陰影覆蓋的比例不定,都會影響影像恢復的成效。因此,藉由先分類光照方向再由輔助的頻譜幅度補償傅立葉轉換後的扭曲頻譜幅度。而我們所提出的方法不僅可提高人臉辨識度與改善覆蓋陰影的區塊還能改善原始的方法。然而,實驗結果與分析明顯呈現我們改良的方法,在光照變化之下,比原始方法更能大幅提升識別的性能。
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.
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