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Face Image Recognition

Face Image Recognition. Face recognition technology works well with most of the shelf PC cameras, generally requiring 320*240 resolution at 3~5 frames per second. Facial recognition software products range in price from US$50 to over US$1000, making one of the cheaper biometric technologies.

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Face Image Recognition

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  1. Face Image Recognition • Face recognition technology works well with most of the shelf PC cameras, generally requiring 320*240 resolution at 3~5 frames per second. • Facial recognition software products range in price from US$50 to over US$1000, making one of the cheaper biometric technologies. • Four primary methods used to identify or verify users by means of facial features, including eigenface, PCA, 2D-PCA, LDA, 2D-LDA, wavelet analysis, neural network, and ad hoc methods. • Singular Value Decomposition and Pattern Recognition. • Fast Fourier Transform and Wavelet Analysis • http://facial-scan.com/facial-scan_technology.htm • http://www-white.media.mit.edu/vismod/demos/facerec

  2. A Face Recognition Flowchart

  3. Face Database • YALE • P. N. Belhumer, J. Hespanha, and D. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Face Recognition, 17(7):711--720, 1997. • YALE B • Georghiades, A.S. and Belhumeur, P.N. and Kriegman, D.J. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Trans. Pattern Anal. Mach. Intelligence 23(6):643-660 (2001). • ORL • Ferdinando Samaria, Andy Harter. Parameterisation of a Stochastic Model for Human Face Identification. Proceedings of 2nd IEEE Workshop on Applications of Computer Vision, Sarasota FL, December 1994 • AR • A.M. Martinez and R. Benavente. The AR Face Database. CVC Technical Report #24, June 1998

  4. Faces From The Same Person

  5. Cumulative Distributions of Same Faces

  6. Faces from Different Persons

  7. Cumulative Distributions of Different Faces

  8. Fingerprint Image Verification/Identification • Each fingerprint is a map of ridges and valleys in the epidermis layer of the skin. • The ridge and valley structures from unique geometric patterns. • A minutiae pattern consisting of ridge endings and bifurcations is unique to each fingerprint. • Most of the contemporary automated fingerprint identification and verification systems (AFIS) are minutiae pattern matching systems. • A modern AFIS is composed of 5 primary modules: (1) Image Enhancement, (2) Image segmentation and Thinning, (3) Minutiae Points Extraction, (4) Core and Delta Localization, and (5) Point Pattern Matching. • A fingerprint forum provided 5 sets of small databases for researchers to evaluate their identification/verification software. • SecuGen EyeD and Veridicom are two leading companies selling both commercial fingerprint identification/verification systems and sensors with resolution 500dpi. Veridicom FPS110 fingerprint reader sensed a 300*300 fingerprint image in a 2cm by 2cm area. • http://www.networkusa.org/fingerprint.shtml • http://bias.csr.unibo.it/fvc2000 • http://bias.csr.unibo.it/fvc2004 • http://www.fpusa.com

  9. FINGERPRINTS.DEMON.NL

  10. FVC 2004

  11. FVC 2004

  12. A Paradigm for Fingerprint Matching

  13. Fingerprints and Their Histograms

  14. Fingerprint Image Processing

  15. Thank You for Your Attention • KoalaAngel wishes you have a wonderful university life • I am from Brisbane, Australia and sleep 16 hours each day but you should not ☆ March 02, 2009

  16. Are They From the Same Person?

  17. Are They the Same Person?

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