Face And Ear Composite Recognition Tool
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Face And Ear Composite Recognition Tool

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My Final year project :) It was used to compare two faces and ears. Used matlab for it.

My Final year project :) It was used to compare two faces and ears. Used matlab for it.

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Face And Ear Composite Recognition Tool Face And Ear Composite Recognition Tool Presentation Transcript

  • Face and Ear Composite Recognition Tool Abhineet Bhamra (0131322804) Ashish Goel (0181322804) Jaideep Singh (0161322804) Karan Gogna (0361322804)
  • Contents
    • Project Goals
    • Introduction to Biometrics
    • Face Biometrics
    • Ear Biometrics
    • Advantages of Ear Biometrics
    • Implementation
    • Work completed
    • Work to be done
    • References
  • Project Goals
    • To use both face and ear recognition techniques in a single tool for enhanced security and flexibility
    • Compare the performance of both biometrics
    • Identify common sources of errors for both techniques
  • Introduction to Biometrics
    • Definition : Automatic identification of a living person based on physiological or behavio u ral characteristics .
    • Behavioral
      • Voice
      • Signature
      • Keystrokes
    • Physiological
      • Fingerprints
      • Hand Geometry
      • Iris
      • Face
      • Ear
  • Face Biometrics
    • Passive physiological method
    • Natural method – humans recognize people by looking at their faces
    • Fast development of new algorithms
    • Still many unsolved problems including compensation of illumination changes and pose invariance
  • Ear Biometrics
    • Human ears have been used as major feature in the forensic science for many years
    • Human ear contains large amount of specific and unique features that allows for human identification
    • Ear images can be easily taken from a distance and without knowledge of the examined person
    • Suitable for security, surveillance, access control and monitoring applications
  • Advantages of Ear Biometrics
    • Ear does not change during human life, and face changes more significantly with age than any other part of human body
    • Colour distribution is more uniform in ear than in human face, iris or retina
      • Not much information is lost while working with the greyscale or binarized images
    • Ear is also smaller than face , which means that it is possible to work faster and more efficiently with the images with the lower resolution
    • Ear images cannot be disturbed by glasses, beard nor make-up. However, occlusion by hair or earrings is possible
  • Implementation
    • Acquiring an image of the subject from scanner/digital camera/video recording
    • Detect the location of any face or ear in the image
    • Analysis of the spatial geometry of distinguishing features of face/ear and generate a template
    • Compare the template with those in the database of known faces/ears
    • Declare match or mismatch depending on the similarity and security configuration
  • Work completed
    • Feature extraction and building a database using PCA – eigenfaces and eigenears approach
    • Recognition of face and ear images by comparison with face and ear databases respectively and calculation of Euclidean distance
    • [Please add some other stuff too that u think we can show]
  • Work to be done
    • Automatic extraction of face and ear from corresponding images
    • Implementation of other algorithms and a comparison of their performance
    • Integration of both face and ear recognition in a single tool
    • Development of GUI
    • Comparison of face and ear as a biometric
    • Identify reasons for error/limitations of the tool developed
  • References (to be updated)
    • John D. Woodward, Jr., Christopher Horn, Julius Gatune, and Aryn Thomas: “ Biometrics - A Look at Facial Recognition ”, RAND Public Safety and Justice, 2003
    • Lammi, Hanna-Kaisa: “ Ear Biometrics ”. Lappeenranta University of Technology, Department of Information Technology, Laboratory of Information Processing, P.O. BOX 20, 53851 Lappeenranta, Finland
    • Burge, M. and Burger, W. “ Ear Biometrics in Computer Vision ”. In the 15th International Conference of Pattern Recognition, ICPR 2000.
    • Wikipedia: http:// en.wikipedia.org/wiki/Biometrics
  • Thank You