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研究生:孫乙任
研究生(外文):Yi-Jen Sun
論文名稱:整合小波轉換、索貝爾運算及正交投影法之人臉辨識系統
論文名稱(外文):Fusion of Wavelet Transform, Sobel Operator and Orthogonal Projection for Face Recognition
指導教授:李祖聖
指導教授(外文):Tzuu-Hseng S. Li
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電機工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:60
中文關鍵詞:人臉辨識
外文關鍵詞:face recognition
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近年來人的身份辨識系統議題與研究越來越蓬勃發展,而其中以生物特徵且非接觸性的人臉影像作為系統識別身份的方法,最具親和與便利性。傳統人臉辨識所使用主成份分析(PCA)、特徵臉(EigenFace)及線性鑑別分析(LDA)等及其衍生的相關演算法,係直接使用整張影像成為向量信號,經過演算學習取得一投射向量擷取出特徵,其數學運算複雜而且繁複。本論文提出一個利用哈氏離散小波轉換(Haar Wavelet Transform),結合邊緣偵測索貝爾運算子(Sobel)所產生人臉灰階梯度變化,再擷取其正交投影信號作為特徵之人臉辨識系統。最後,採用奧立為特實驗室(Olivetti Research Lab, ORL)人臉資料庫,來驗證本文提出的人臉辨識系統之可行性與有效性。
Study of human face recognition system has grown vigorously for last decades. The biometrics of human face is an important feature in the identity authentication. The traditional principal component analysis (PCA), Eigenface, and linear decision algorithm (LDA) operate directly on a whole pattern represented as a vector and acquire a set of projection vectors to extract global features from given training patterns. The computation loads in these methods are heavy. In this thesis, a novel fusion algorithm of the wavelet transform, Sobel operator and orthogonal projection is proposed for human face recognition, where the Haar wavelet transform is utilized to reduce the dimension of images, the Sobel operator is adopted to extract facial features, and the orthogonal projection is presented to perform feature transformation and face recognition. The Olivetti Research Lab (ORL) face database is adopted to demonstrate the feasibility and effectiveness of the proposed face recognition system.
中文摘要Ⅰ
英文摘要II
誌謝Ⅲ
目錄IV
圖目錄VI
表目錄VIII
第一章.緒論1
1.1研究動機1
1.2文獻回顧2
1.2.1主要成份分析法2
1.2.2線性鑑別分析法7
1.3本文架構10
第二章.小波轉換12
2.1小波轉換理論12
2.2離散小波轉換13
2.2.1多層解析空間14
2.2.2Haar小波轉換14
2.3Haar小波轉換應用18
2.3.1影像Haar小波轉換19
2.3.2Haar小波轉換實驗結果21
第三章.人臉特徵參數擷取24
3.1邊緣偵測理論24
3.1.1拉普拉斯運算子25
3.1.2索貝爾運算子27
3.2正交投影29
3.3辨識決策方式31
第四章.人臉辨識法與實驗35
4.1人臉影像資料庫35
4.2人臉辨識法36
4.2.1原始影像實驗41
4.2.2一階Haar影像實驗42
4.2.3二階Haar影像實驗44
4.3實驗結果討論45
第五章.結論與未來研究方向57
5.1結論57
5.2未來研究方向58
參考文獻59
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[14]林宸生,應用於LCD上的定位研究. [Online]. Available: http://cslin.auto.fcu.edu.tw/oe/oe/lcd/index1.htm
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[18]D. X. Shuicheng, Y. L. Zhang, M. Li, W. Ma, Z. Liu and H. Zhang, “Parallel Image Matrix Compression for Face Recognition,” in Proceedings of the 11th International Multimedia Modelling Conference, 2005, Jan. 2005, pp. 232–238.
[19]鍾國亮, 影像處理與電腦視覺, 東華, 2006.
[20]洪國勝、江國軍、龍國忠、洪月裡, C++ Builder 6 程式設計快樂上手, 旗標, 2002.
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