Illumination normalized face image for face recognition

Jaepil Ko; Eunju Kim; Heyran Byun

doi:10.1007/3-540-70659-3_68

Illumination normalized face image for face recognition

Jaepil Ko, Eunju Kim, Heyran Byun

College of Computing

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

2 Citations (Scopus)

Abstract

A small change in illumination produces large changes in appearance of face even when viewed in fixed pose. It makes face recognition more difficult to handle. To deal with this problem, we introduce a simple and practical method based on the multiple regression model, we call it ICR (Illumination Compensation based on the Multiple Regression Model). We can get the illumination-normalized image of an input image by ICR. To show the improvement of recognition performance with ICR, we applied ICR as a preprocessing step. We achieved better result with the method in preprocessing point of view when we used a popular technique, PCA, on a public database and our database.

Original language	English
Title of host publication	Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings
Editors	Terry Caelli, Adnan Amin, Robert P.W. Duin, Dick de Ridder, Mohamed Kamel
Publisher	Springer Verlag
Pages	654-661
Number of pages	8
ISBN (Print)	3540440119, 9783540440116
DOIs	https://doi.org/10.1007/3-540-70659-3_68
Publication status	Published - 2002
Event	Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002 - Windsor, Canada Duration: 2002 Aug 6 → 2002 Aug 9

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2396
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002
Country/Territory	Canada
City	Windsor
Period	02/8/6 → 02/8/9

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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10.1007/3-540-70659-3_68

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Ko, J., Kim, E., & Byun, H. (2002). Illumination normalized face image for face recognition. In T. Caelli, A. Amin, R. P. W. Duin, D. de Ridder, & M. Kamel (Eds.), Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings (pp. 654-661). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2396). Springer Verlag. https://doi.org/10.1007/3-540-70659-3_68

Ko, Jaepil ; Kim, Eunju ; Byun, Heyran. / Illumination normalized face image for face recognition. Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings. editor / Terry Caelli ; Adnan Amin ; Robert P.W. Duin ; Dick de Ridder ; Mohamed Kamel. Springer Verlag, 2002. pp. 654-661 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Illumination normalized face image for face recognition",

abstract = "A small change in illumination produces large changes in appearance of face even when viewed in fixed pose. It makes face recognition more difficult to handle. To deal with this problem, we introduce a simple and practical method based on the multiple regression model, we call it ICR (Illumination Compensation based on the Multiple Regression Model). We can get the illumination-normalized image of an input image by ICR. To show the improvement of recognition performance with ICR, we applied ICR as a preprocessing step. We achieved better result with the method in preprocessing point of view when we used a popular technique, PCA, on a public database and our database.",

author = "Jaepil Ko and Eunju Kim and Heyran Byun",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.; Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002 ; Conference date: 06-08-2002 Through 09-08-2002",

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Ko, J, Kim, E & Byun, H 2002, Illumination normalized face image for face recognition. in T Caelli, A Amin, RPW Duin, D de Ridder & M Kamel (eds), Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2396, Springer Verlag, pp. 654-661, Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002, Windsor, Canada, 02/8/6. https://doi.org/10.1007/3-540-70659-3_68

Illumination normalized face image for face recognition. / Ko, Jaepil; Kim, Eunju; Byun, Heyran.
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings. ed. / Terry Caelli; Adnan Amin; Robert P.W. Duin; Dick de Ridder; Mohamed Kamel. Springer Verlag, 2002. p. 654-661 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2396).

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

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T1 - Illumination normalized face image for face recognition

AU - Ko, Jaepil

AU - Kim, Eunju

AU - Byun, Heyran

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N2 - A small change in illumination produces large changes in appearance of face even when viewed in fixed pose. It makes face recognition more difficult to handle. To deal with this problem, we introduce a simple and practical method based on the multiple regression model, we call it ICR (Illumination Compensation based on the Multiple Regression Model). We can get the illumination-normalized image of an input image by ICR. To show the improvement of recognition performance with ICR, we applied ICR as a preprocessing step. We achieved better result with the method in preprocessing point of view when we used a popular technique, PCA, on a public database and our database.

AB - A small change in illumination produces large changes in appearance of face even when viewed in fixed pose. It makes face recognition more difficult to handle. To deal with this problem, we introduce a simple and practical method based on the multiple regression model, we call it ICR (Illumination Compensation based on the Multiple Regression Model). We can get the illumination-normalized image of an input image by ICR. To show the improvement of recognition performance with ICR, we applied ICR as a preprocessing step. We achieved better result with the method in preprocessing point of view when we used a popular technique, PCA, on a public database and our database.

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Ko J, Kim E, Byun H. Illumination normalized face image for face recognition. In Caelli T, Amin A, Duin RPW, de Ridder D, Kamel M, editors, Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops SSPR 2002 and SPR 2002, Proceedings. Springer Verlag. 2002. p. 654-661. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-70659-3_68

Illumination normalized face image for face recognition

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