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URN etd-0217109-142356 Statistics This thesis had been viewed 2159 times. Download 1390 times. Author Ching-Chou Hsieh Author's Email Address No Public. Department Mechanical Engineering Year 2008 Semester 1 Degree Master Type of Document Master's Thesis Language zh-TW.Big5 Chinese Page Count 47 Title Face Recognition based on Artificial Immune Network and Principal component analysis Keyword genetic algorithms face recognition artificial immune network principal component analysis antigen space immune response immune response antigen space principal component analysis artificial immune network face recognition genetic algorithms Abstract Recently, because of the necessity of social security, the research about personal identification using face recognition is widely studied. Among lots of papers for face recognition, there are some using facial features in order to achieve higher recognition accuracy.
This thesis proposes a new immune algorithm that was called Artificial Immune Network unlike others. Picks up the person face the principal components analysis (principal component analysis) to take the antigen, again using the antigen space in the antibody and the antigen union biggest immune response concept, the application genetic algorithm, constructs its corresponding in view of each person's face image the kind of immunity network, finally by the person face information ORL Face Database confirmation, can obtain the extremely good identification result.
Advisor Committee Guan-Chun Luh - advisor
Chun-Yin Wu - co-chair
Ming-Chuan Wu - co-chair
Files Date of Defense 2009-01-05 Date of Submission 2009-02-17