Two-dimensional canonical correlation analysis for face image processing and recognition

• Autorzy: Kukharev G. , Kamenskaya E.
• Języki publikacji: EN

Abstrakty

EN

Paper presents the method of two-dimensional canonical correlation analysis (2DCCA) as applied to image processing and biometrics. Method is based on representing the image as the sets of its rows (r) and columns (c) and implementation of CCA using these sets (for these reason we named the method as CCArc). CCArc features simple implementation and lesser complexity than other known approaches. In applications to biometrics CCArc is suitable to solving the problems when dimension of images (dimension of feature space) is greater than number of images, i.e. Small Sample Size problem (SSS). Demonstrated high efficiency of CCArc method for a number of computer experiments. Experiments itself are described with compact notation allowing to use its results in the framework of meta-analysis.

Słowa kluczowe

EN

two-dimensional canonical correlation analysis (2DCCA); space of canonical variates; feature space dimensionality reduction; biometrics

PL

dwuwymiarowa analiza korelacji kanonicznej; przetwarzanie obrazów twarzy; funkcja redukcji wymiarowości przestrzeni; biometria

• Wydawca: Komisja Informatyki Polskiej Akademii Nauk, Oddział w Gdańsku
• Czasopismo: Metody Informatyki Stosowanej
• Rocznik: 2009
• Tom: nr 3 (20)
• Strony: 103--112
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Kukharev G.

autor

Kamenskaya E.

• West Pomeranian University of Technology, Szczecin, Poland, Faculty of Computer Science and Information Technology

Bibliografia

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• [3] Dong Yi, Rong Liu, RuFeng Chu, Zhen Lei and Stan Z. Li, Face Matching Between Near Infrared and Visible Light Images, Lecture Notes in Computer Science, Volume 4642, 2007, pp. 523-530.
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• [5] Szaber M., Kamenskaya E. Systemy rozpoznawania twarzy dla obrazów widzialnych i podczerwieni z wykorzystaniem CCA. Metody Informatyki Stosowanej, No. 3/2008, Vol. 16, 2008, pp. 223-236.
• [6] 10. ISO/IEC JTC 1/SC 37 N 506: Biometric Data Interchange Formats, Part 5: Face Image Data – www.icao.int/mrtd/download/technical.cfm
• [7] Magnus Borga. Canonical Correlation a Tutorial. January 12, 2001. http://www.imt.liu.se/~magnus/cca/tutorial/tutorial.pdf.
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• [9] Zou Cai-rong, Sun Ning, Ji Zhen-hai, Zhao Li. 2DCCA: A Novel Method for Small Sample Size Face Recognition. IEEE Workshop on Application of Computer Vision, WACV’07, 2007, pp. 43-47.
• [10] Kukharev G., Forczmanski P. Facial Images Dimensionality Reduction and Recognition by Means of 2DKLT. Machine Graphics & Vision, Vol.16, No. 3/4, 2007, pp. 401-425.
• [11] Кухарев Г.А., Щеголева Н.Л. Системы распознавания человека по изображению лица. (Face Recognition Systems) Монография: Из-во СПбГЭТУ (ЛЭТИ), СПб, 2006, 176 с.
• [12] Кухарев Г.А. Поиск изображений лиц в больших базах данных. Журнал «МИР ИЗМЕРЕНИЙ» 4(98) 2009, с. 22-30.
• [13] Philips P.J., Wechler H., Huang J., Rauss P. The FERET Database and Evaluation Procedure for Face Recognition algorithms. Image and Vision Computing, Vol. 16, No. 5, 1998, pp. 295-306.