Bong, D.B.L (2016) Analysis of bit-plane images by using principal component on face and palmprint database. Pertanika Journal of Science and Technology, 24 (1). pp. 191-203. ISSN 0128-7680Full text not available from this repository.
The bit-plane feature extraction approach has lately been introduced for face and palm-print recognition. This approach decomposes an 8-bit grey level image into eight groups of bit layers. The assumption of this approach is that the highest order of a bit-plane decomposition, which has the most significant bits of all pixels, contains the most biometric features. Nonetheless, most research has identified bit-plane images illustratively. Hence, in order to endorse the assumption, we performed an analysis on face and palm-print images to identify the bit-plane that contributes most significantly to the recognition performance. Analysis was done based on Principal Component Analysis (PCA). The first principal component was applied as it is defined for the largest possible variance of the data. Next, Euclidean distance was calculated for matching performance. It was observed that bit-plane 6 and 7 contributed significantly to recognition performance. © 2016 Universiti Putra Malaysia Press.
|Uncontrolled Keywords:||Bit-plane, Principal Component Analysis, face recognition, palm-print recognition, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak|
|Subjects:||T Technology > T Technology (General)|
|Divisions:||Academic Faculties, Institutes and Centres > Faculty of Engineering|
|Depositing User:||Tay Kai Meng|
|Date Deposited:||10 Feb 2016 03:10|
|Last Modified:||21 Oct 2016 02:49|
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