A wavelet-based face recognition system using partial information

H. F. Neo; C. C. Teo; Andrew B.J. Teoh

doi:10.1007/978-3-642-17277-9_44

A wavelet-based face recognition system using partial information

H. F. Neo, C. C. Teo, Andrew B.J. Teoh

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper aims to integrate part-based feature extractor, namely Non-negative matrix factorization (NMF), Local NMF and Spatially Confined NMF in wavelet frequency domain. Wavelet transform, with its approximate decomposition is used to reduce the noise and produce a representation in the low frequency domain, and hence making the facial images insensitive to facial expression and small occlusion. 75% ratio of full-face images are used for training and testing since they contain sufficient information as reported in a previous study. Our experiments on Essex-94 Database demonstrate that feature extractors in wavelet frequency domain perform better than without any filters. The optimum result is obtained for SFNMF of r*= 60 with Symlet orthonormal wavelet filter of order 2 in the second decomposition level. The recognition rate is equivalent to 98%.

Original language	English
Title of host publication	Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings
Pages	427-436
Number of pages	10
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-17277-9_44
Publication status	Published - 2010
Event	6th International, Symposium on Visual Computing, ISVC 2010 - Las Vegas, NV, United States Duration: 2010 Nov 29 → 2010 Dec 1

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	6455 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th International, Symposium on Visual Computing, ISVC 2010
Country/Territory	United States
City	Las Vegas, NV
Period	10/11/29 → 10/12/1

Bibliographical note

Funding Information:
Acknowledgments. The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114.

Funding Information:
The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-17277-9_44

Cite this

Neo, H. F., Teo, C. C., & Teoh, A. B. J. (2010). A wavelet-based face recognition system using partial information. In Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings (PART 3 ed., pp. 427-436). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6455 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-17277-9_44

Neo, H. F. ; Teo, C. C. ; Teoh, Andrew B.J. / A wavelet-based face recognition system using partial information. Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings. PART 3. ed. 2010. pp. 427-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

@inproceedings{8f0dbe5be3334029b1b9848ff62fa3a4,

title = "A wavelet-based face recognition system using partial information",

abstract = "This paper aims to integrate part-based feature extractor, namely Non-negative matrix factorization (NMF), Local NMF and Spatially Confined NMF in wavelet frequency domain. Wavelet transform, with its approximate decomposition is used to reduce the noise and produce a representation in the low frequency domain, and hence making the facial images insensitive to facial expression and small occlusion. 75% ratio of full-face images are used for training and testing since they contain sufficient information as reported in a previous study. Our experiments on Essex-94 Database demonstrate that feature extractors in wavelet frequency domain perform better than without any filters. The optimum result is obtained for SFNMF of r*= 60 with Symlet orthonormal wavelet filter of order 2 in the second decomposition level. The recognition rate is equivalent to 98%.",

author = "Neo, {H. F.} and Teo, {C. C.} and Teoh, {Andrew B.J.}",

note = "Funding Information: Acknowledgments. The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114. Funding Information: The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114.; 6th International, Symposium on Visual Computing, ISVC 2010 ; Conference date: 29-11-2010 Through 01-12-2010",

year = "2010",

doi = "10.1007/978-3-642-17277-9_44",

language = "English",

isbn = "3642172768",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 3",

pages = "427--436",

booktitle = "Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings",

edition = "PART 3",

}

Neo, HF, Teo, CC & Teoh, ABJ 2010, A wavelet-based face recognition system using partial information. in Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 6455 LNCS, pp. 427-436, 6th International, Symposium on Visual Computing, ISVC 2010, Las Vegas, NV, United States, 10/11/29. https://doi.org/10.1007/978-3-642-17277-9_44

A wavelet-based face recognition system using partial information. / Neo, H. F.; Teo, C. C.; Teoh, Andrew B.J.
Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings. PART 3. ed. 2010. p. 427-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6455 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A wavelet-based face recognition system using partial information

AU - Neo, H. F.

AU - Teo, C. C.

AU - Teoh, Andrew B.J.

N1 - Funding Information: Acknowledgments. The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114. Funding Information: The authors wish to thank Ministry Of Science, Technology and Innovation Malaysia. This work is supported by the e-Science grant no. 01-02-01-SF0114.

PY - 2010

Y1 - 2010

N2 - This paper aims to integrate part-based feature extractor, namely Non-negative matrix factorization (NMF), Local NMF and Spatially Confined NMF in wavelet frequency domain. Wavelet transform, with its approximate decomposition is used to reduce the noise and produce a representation in the low frequency domain, and hence making the facial images insensitive to facial expression and small occlusion. 75% ratio of full-face images are used for training and testing since they contain sufficient information as reported in a previous study. Our experiments on Essex-94 Database demonstrate that feature extractors in wavelet frequency domain perform better than without any filters. The optimum result is obtained for SFNMF of r*= 60 with Symlet orthonormal wavelet filter of order 2 in the second decomposition level. The recognition rate is equivalent to 98%.

AB - This paper aims to integrate part-based feature extractor, namely Non-negative matrix factorization (NMF), Local NMF and Spatially Confined NMF in wavelet frequency domain. Wavelet transform, with its approximate decomposition is used to reduce the noise and produce a representation in the low frequency domain, and hence making the facial images insensitive to facial expression and small occlusion. 75% ratio of full-face images are used for training and testing since they contain sufficient information as reported in a previous study. Our experiments on Essex-94 Database demonstrate that feature extractors in wavelet frequency domain perform better than without any filters. The optimum result is obtained for SFNMF of r*= 60 with Symlet orthonormal wavelet filter of order 2 in the second decomposition level. The recognition rate is equivalent to 98%.

UR - http://www.scopus.com/inward/record.url?scp=78650797357&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650797357&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-17277-9_44

DO - 10.1007/978-3-642-17277-9_44

M3 - Conference contribution

AN - SCOPUS:78650797357

SN - 3642172768

SN - 9783642172762

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 427

EP - 436

BT - Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings

T2 - 6th International, Symposium on Visual Computing, ISVC 2010

Y2 - 29 November 2010 through 1 December 2010

ER -

Neo HF, Teo CC, Teoh ABJ. A wavelet-based face recognition system using partial information. In Advances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings. PART 3 ed. 2010. p. 427-436. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-17277-9_44

A wavelet-based face recognition system using partial information

Abstract

Publication series

Other

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this