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研究生:廖俊熒
研究生(外文):Chun-Ying Liao
論文名稱:數位人臉過度亮光影像的膚色重建研究
論文名稱(外文):Digital Processing for Reconstruction of Human Facial Reflection Images
指導教授:李福星李福星引用關係陳佑冠
指導教授(外文):Fu-shin LeeYu-Kumg Chen
學位類別:碩士
校院名稱:華梵大學
系所名稱:機電工程研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:95
語文別:中文
論文頁數:42
中文關鍵詞:亮光膚色人臉辨識色彩空間膚色區隔影像處理
外文關鍵詞:specualr reflectionface recognitioncolor spaceskin segmentationimage processing.
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在人臉的數位影像裡,常因為光線照射強度、數位取像設備參數設定和光源的角度問題,而取到部份過度亮光的人臉數位影像,對後續人臉影像處理辨識系統容易造成誤判。因此,本論文利用一般膚色區隔演算法,結合Sobel演算法獲得邊界影像資訊,以及區域擴散法,提出一解決人臉過度亮光影像問題之影像處理策略。本文所提演算法可重建人臉過度亮光部份的膚色影像,是以其後影像處理可擷取人臉上特徵部位之正確位置,如眼睛、眉毛、嘴巴、甚至是鼻子,藉此大幅提昇人臉辨識系統辨識正確率。經由本研究實驗證明本文所提影像處理策略也適用於不同膚色人種之人臉膚色過度亮光部份影像重建。
During the digital signal processing stages for human facial images, there exist various factors such as lighting source intensities, digital camera settings, and light incident as well as reflecting angles employed in the applications may cause partial over-bright abnormal specular reflections on the processed facial images. These erroneous images would definitely lead to certain misjudges during post-processing stages, for example, the human face recognition applications. Hence, the object of this research is to establish a systematic algorithm to reconstruct the over-bright abnormal specular reflection regions back to the regular facial colors as they should be. Basically, the proposed strategy first employs the conventional human skin color space segmentation methods associated with the Sobel computation technique to obtain the facial edge information, and then implement the similar region growing method to recover the over-bright specular reflections within the facial images.
Consequently, the proposed algorithm has been verified in this thesis for reconstructing several facial images from their over-bright specular reflections. As well, the outcome of this research could be adopted in extracting facial features from human facial images with high credibility, since most possible over-bright specular reflections have already recovered. In addition, the algorithm has also been carried out for different facial skin color images, and the processed results demonstrate the effectiveness and computational advantages of this approach.
目錄

摘要Ⅰ
ABSTRACT Ⅱ
目錄 Ⅲ
表錄 Ⅴ
圖錄 Ⅵ
第一章 緒論 1
1.1 研究動機 1
1.2 文獻探討 1
1.3 研究成果 2
1.4 論文架構 3
第二章 色系的選擇 5
2.1 RGB色彩空間 5
2.2 HSV色彩空間 6
2.3 YUV色彩空間 9
2.4 YCbCr色彩空間 9
2.5 本章結論 10
第三章 膚色的區隔 11
3.1 平均值與標準差 11
3.2 雜訊處理 12
3.3 各種色系下的膚色範圍 13
3.3.1 正規化RGB色彩空間 13
3.3.2 HSV色彩空間 14
3.3.3 YCbCr色彩空間 15
3.4 膚色區隔演算法 15
3.5 本章結論 16
第四章 過度亮光膚色的重建 17
4.1 過度亮光膚色的潛在位置 17
4.2 邊緣偵測 17
4.3 過度亮光膚色重建演算法 19
4.4 膚色還原演算法 21
4.5 本章結論 23
第五章 分析 25
5.1 色彩空間的選擇 25
5.2 鄰近矩陣之視窗大小的選擇 26
5.2.1 膚色資訊鄰近矩陣大小的選擇 26
5.2.2 邊緣資訊鄰近矩陣大小的選擇 27
5.2.3 時間的分析 30
5.3 邊緣資訊門檻值的分析 31
5.4 本章結論 36
第六章 實驗結果 37
6.1 門檻值的決定 37
6.2 實驗樣本及結果 37
第七章 結論及未來展望 40
參考文獻 41
參考文獻


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