کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361810 | 870409 | 2005 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The equivalence of two-dimensional PCA to line-based PCA
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
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چکیده انگلیسی
The state-of-the-art in human face recognition is the subspace methods originated by the Principal Component Analysis (PCA), the Eigenfaces of the facial images. Recently, a technique called Two-dimensional PCA (2DPCA) was proposed for human face representation and recognition. It was developed for image feature extraction based on 2D matrices as opposed to the standard PCA, which is based on 1D vectors. In this note, we show that 2DPCA is equivalent to a special case of an existing feature extraction method, block-based PCA, which has been used for face recognition in a number of systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 26, Issue 1, 1 January 2005, Pages 57-60
Journal: Pattern Recognition Letters - Volume 26, Issue 1, 1 January 2005, Pages 57-60
نویسندگان
Liwei Wang, Xiao Wang, Xuerong Zhang, Jufu Feng,