Homogeneous and Non-homogeneous Polynomial Based Eigenspaces to Extract the Features on Facial Images


Arif Muntasa, Journal of Information Processing Systems Vol. 12, No. 4, pp. 591-611, Dec. 2016  

https://doi.org/10.3745/JIPS.01.0011
Keywords: Eigenspaces, feature extraction, Homogeneous, Non-homogeneous
Fulltext:

Abstract

High dimensional space is the biggest problem when classification process is carried out, because it takes longer time for computation, so that the costs involved are also expensive. In this research, the facial space generated from homogeneous and non-homogeneous polynomial was proposed to extract the facial image features. The homogeneous and non-homogeneous polynomial-based eigenspaces are the second opinion of the feature extraction of an appearance method to solve non-linear features. The kernel trick has been used to complete the matrix computation on the homogeneous and non-homogeneous polynomial. The weight and projection of the new feature space of the proposed method have been evaluated by using the three face image databases, i.e., the YALE, the ORL, and the UoB. The experimental results have produced the highest recognition rate 94.44%, 97.5%, and 94% for the YALE, ORL, and UoB, respectively. The results explain that the proposed method has produced the higher recognition than the other methods, such as the Eigenface, Fisherface, Laplacianfaces, and O-Laplacianfaces


Statistics
Show / Hide Statistics

Statistics (Past 3 Years)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Muntasa, A. (2016). Homogeneous and Non-homogeneous Polynomial Based Eigenspaces to Extract the Features on Facial Images . Journal of Information Processing Systems, 12(4), 591-611. DOI: 10.3745/JIPS.01.0011.

[IEEE Style]
A. Muntasa, "Homogeneous and Non-homogeneous Polynomial Based Eigenspaces to Extract the Features on Facial Images ," Journal of Information Processing Systems, vol. 12, no. 4, pp. 591-611, 2016. DOI: 10.3745/JIPS.01.0011.

[ACM Style]
Arif Muntasa. 2016. Homogeneous and Non-homogeneous Polynomial Based Eigenspaces to Extract the Features on Facial Images . Journal of Information Processing Systems, 12, 4, (2016), 591-611. DOI: 10.3745/JIPS.01.0011.