Advances in Biometric Person Authentication: International by Matti Pietikäinen, Abdenour Hadid (auth.), Stan Z. Li,

By Matti Pietikäinen, Abdenour Hadid (auth.), Stan Z. Li, Zhenan Sun, Tieniu Tan, Sharath Pankanti, Gérard Chollet, David Zhang (eds.)

This ebook constitutes the refereed lawsuits of the overseas Workshop on Biometric attractiveness structures, IWBRS 2005, held in Beijing, China in October 2005 in the scope of ICCV 2005, the foreign convention on laptop imaginative and prescient. This workshop combines the once a year chinese language convention on Biometric reputation (Sinobiometrics 2005).

The 32 revised complete papers have been rigorously reviewed and chosen from a hundred thirty submissions. The papers tackle the issues of computerized and trustworthy authentication of people in face, iris, fingerprint, palmprint, speaker, writing and different biometrics, and give a contribution new rules to investigate and improvement of trustworthy and useful ideas for biometric authentication.

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Extra info for Advances in Biometric Person Authentication: International Wokshop on Biometric Recognition Systems, IWBRS 2005, Beijing, China, October 22-23, 2005. Proceedings

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600 frontal face images corresponding to 200 subjects are extracted from the database for the experiments - each subject has three images of size 256×384 with 256 gray levels. The images were captured at different photo sessions so that they display variations in illumination and facial expression. Two images of each subject are randomly chosen for training, and the remaining one is used for testing. The following procedures were applied to normalize the face images prior to the experiments: • • • • The centres of the eyes of each image are manually marked Each image is rotated and scaled to align the centre of the eyes Each face image is cropped to the size of 64×64 to extract the facial region Each cropped face image is normalized to zero mean and unit variance Figure 3 shows the sample images from the database.

Y ' = [ yc − y0, yc − y1...... yc − yq −1 ]T (8) ' Once the compensated plane Y is available, the illumination corrected image can be achieved: (9) P' = P + Y ' The implement of ICR algorithm is rather simple. However, since it only considers the compensation using illumination density plane in one direction, it is much more restricted and not robust. For these reasons, usually it does not single out to apply for illumination correction for face images. 1 Discussion Though the AT or ICR algorithm does have effect on illumination normalization and good performances can be observed when they are applied to face normalization, see [9]-[10] for detail.

Rauss, and S. Rizvi: The FERET Evaluation Methodology for Face Recognition Algorithms, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, Oct. 2000. 9. Bo Cao, Shiguang Shan, Xiaohua Zhang, Wen Gao: Baseline Evaluations on the CASPEAL-R1 Face Database, SinoBiometrics 2004, pp. 370-378. 10. R. Brunelli, T. Poggio: Face Recognition: Features vs. Templates, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15, No. 10, pp. 1042-1053, Oct. 1993. 11. M. Turk and A.

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