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13.face recog

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13.face recog

  1. 1. Face Recognition B.RANJITHA REDDY , ANUSHA. K
  2. 2. Introduction to BiometricsThe term "biometrics" is derived fromthe Greek words bio (life) and metric(to measure). The biometric providesmost secure level of authorization.
  3. 3.  Types Of Biometrics Physiological.BehavioralPhysiological.: Physiological are related to the shape of the body. Examples include, fingerprint, face recognition , DNA, hand and palm geometry , iris recognition.
  4. 4. FINGER PRINT SPEECH RECOGNITION
  5. 5. History ofFacial Recognition • Late 1980s: Research • Mid 1990s: Commercialization • Current - Authentication - ID - Law Enforcement
  6. 6. Theory Behind Facial Recognition I• Eigenface Technology:• Local Feature Analysis: 32-50 blocks
  7. 7. Theory Behind Facial Recognition II• Identalink TrueFace
  8. 8. Eye Identification Using Neural Networks • 2 Neural Networks - Finding the eyes - Identifying the person• Small vs Large Window
  9. 9. Infrared Images and Eigenfaces I • Training and Test set of images • Eigenface
  10. 10. Infrared Images and Eigenfaces II• Threshold Euclidean Distance
  11. 11. Scale-Space Approach from Profiles I• Profile Line• Locate Nose Tip
  12. 12. Scale-Space Approach from Profiles II• Locate Extrema (1, 2, 4-9) and Inflection Points (10 –12)• Feature Vectors• Euclidean Distance
  13. 13. Morphological Operations on Profiles I• 2-D shape represented by 1-D function • Dilation • Erosion
  14. 14. Morphological Operations on Profiles II• 3 Shapes: A, M1, M2• 3 feature vectors - centroid  face - centroid  hair• Minimal Euclidean Distancebetween 2 profile images
  15. 15. Advantages OverCompeting Systems• Voluntary Action vs Passive Usage• Data Acquisition• Environment interfacing is very less.• Cost is reasonable.
  16. 16. APPLICATIONSFacial RecognitionHand GeometryIris ScanRetina ScanVascular PatternsFinger printDNA
  17. 17. Project Selection / Outline • Algorithm: MATLAB implementation of face recognition profile matching • Database: MATLAB development of file system • Data Acquisition: Multimedia Lab video camera or digital camera
  18. 18. References• Ross Cutler, “Face Recognition Using Infrared Images and Eigenfaces”, April 1996.• Age Eide, Christer Jahren, Stig Jorgensen, Thomas Lindblad, Clark S. Lindsey, and Kare Osterud, “Eye Identification for Face Recognition with Neural Netowrks”, 1996.• Zdravko Liposcak and Sven Loncaric, “Face Recognition from Profiles Using Morphological Operators,” 1998.• Zdravko Liposcak and Sven Loncaric, “A Scale-Space Approach to Face Recognition from Profiles,” 1999.

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