Face recognition system based on orthogonal polynomials

被引：0

作者：

Krishnamoorthy, R. ^{[1
]}

Bhavani, R. ^{[1
]}

机构：

[1] Department of Computer Science and Engineering, Annamalai University

来源：

Journal of Applied Sciences | 2007年 / 7卷 / 01期

关键词：

Edge extraction; Face recognition; operators; Orthogonal polynomials; Point-spread;

D O I：

10.3923/jas.2007.109.114

中图分类号：

学科分类号：

摘要：

A new computational model based face recognition system with edge extraction scheme is presented in this research. The proposed model has been built centering on some simple point spread operators, which are easily constructed from a set of orthogonal polynomials. One speciality of these point-spread operators is that they can be used in transforming vis-à-vis approximating 2D monochrome image regions. Also a complete set of difference operators are configured from these point-spread operators. Initially, we detect the face from the given input image using an edge extraction scheme, derived as maximizing the signal to noise ratio due to operator's response supported by the proposed orthogonal polynomials. Simple procedures are derived to compute characteristic subsets of coefficients of the proposed transformation that represent important features, are considered for face recognition on the face detected input image. The prposed face recognition system is tested with the Yale database and also compared with Discrete Cosine Transform based face recognition system, Principle Component Analysis based face recognition system and fisher face recognition system. © 2007 Asian Network for Scientific Information.

引用

页码：109 / 114

页数：5

共 19 条

[11]

Krishnamoorthy R., Bhattacharyya P., Statistical Experiments Approach to Transform Coding, pp. 155-160, (1997)

[12]

Krishnamoorthy R., Bhattacharyya P., Color edge extraction using orthogonal polynomial based zero crossing scheme, Intl. J. Inform. Sci., 112, pp. 51-65, (1998)

[13]

Liu C., Wechsler H., A Gabour feature classifier for face recognition, 8th IEEE International Conference on Computer Vision, pp. 270-275, (2001)

[14]

Paffenberger R.C., Patterson H.G., Statistical Methods for Business and Economics, (1987)

[15]

Teixeira M.L., Beveridge J.R., An implementation and study of the moghaddam and pentland intrapersonal/ extrapersonal image difference face recognition algorithm, (2003)

[16]

Tian Y.L., Brown L., Hampapur A., Pankanti S., Senior A., Bolle R., Real world real-time automatic recognition of facial expressions, IEEE Workshop on Performance Evaluation of Tracking and Surveillance, (2003)

[17]

Turk M., Pentland A., Face Recognition using Eigen faces, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 586-591, (1991)

[18]

Winkott L., Fellous J., Kruger N., Von der Malsburg C., Face Recognition by elastic bunch graph matching, IEEE Transaction on Pattern Analysis and Machine Imtelligence, 19, pp. 775-779, (1997)

[19]

Ziad M.H., Levine M.D., Face recognition using the discrete cosine Transform, Intl. J. Computer Vision, 4, pp. 167-188, (2001)

← 1 2 →