BC4202 Biometric Data Processing Syllabus:
BC4202 Biometric Data Processing Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To understand the basics of Biometric Data processing
To model and visualize the transformation of image
To understand the evolution of object detection
To learn the computational methods involved in the biometric systems
UNIT I INTRODUCTION TO BIOMETRIC DATA PROCESSING
Biometric Databases – Biometric traits – Biometric Modalities – Principles of Biometrics: Behavior and Physiology, Data Acquisition, Liveness Detection, Active Biometric Traits- Voice Biometrics, Handwriting Biometrics , Gait Biometrics, Other Active Traits, Passive Biometric Traits- Fingerprint Biometrics, Iris Biometrics, Face Biometrics, ECG Biometrics, Other Passive Traits, Multimodal biometrics -Taxonomy of multimodal biometrics, fusion levels – Biometric Standards.
UNIT II IMAGE PROCESSING FUNDAMENTALS AND OPERATIONS OF BIOMETRIC SYSTEM
Image processing and Basic image operations: – pattern recognition/statistics, Error types. image, acquisition, type, point operations, Geometric transformations. Linear interpolation, brightness correction, histogram, Convolution, linear/non-linear filtering, Guassian, Median, Min, gray level reduction. Special filters, enhancement filter, Laplacian, unsharp masking, high boost filtering, sharpening special filtering, Edge detection, DFT , inverse of DFT. Operations of a biometric system – verification and identification, performance of a biometric system, FAR, FRR, GAR, ERR, DET and ROC curve, Failure to Acquire (FTA), Failure to Enroll (FTE), applications of biometrics, characteristics.
UNIT III OBJECT DETECTION AND FACE RECOGNITION
Object Detection- Boundary descriptors –Region descriptors –moving object detection –tracking moving features- Moving extraction and description-Texture description –classification – segmentation. Face Recognition – Eigenfaces (PCA), Linear Discriminant Analysis (LDA) and Fisher faces, Independent Component Analysis (ICA), Neural Networks (NN) and Support Vector Machines (SVM), Kernel Methods, Face biometric database
UNIT IV FINGERPRINT AND IRIS RECOGNITION
Fingerprint recognition – Sensing, feature extraction, Enhancement and binarization, Minutiae extraction, matching – correlation based methods, minutiae based methods, ridge feature based methods, performance evaluation, synthetic fingerprint generation IRIS recognition system, Active Contours, Flexible Generalized Embedded Coordinates, Fourier based Trigonometry and Correction for Off-Axis Gaze, Detecting and excluding eyelashes by Statistical Inference, Alternative Score Normalization Rules
UNIT V 3D BIOMETRIC and BIOMETRIC DATA APPLICATIONS
Classification of 3D biometric imaging methods -3D biometric Technologies- 3D palm print capturing systems-3D information in palm print- Feature Extraction from 3D palm print –matching and fusion. Mobile Biometrics- Biometric Application Design – Biometrics in society
COURSE OUTCOMES:
CO1: Explain the principles and types of biometric data processing
CO2: Use Image processing operations for biometrics
CO3: Apply techniques required for object detection and face recognition
CO4: Develop techniques required for fingerprint and iris recognition
CO5: Design and evaluate biometric applications
TOTAL: 45 PERIODS
REFERENCES
1. Ruud M. Bolle, Sharath Pankanti, Nalini K. Ratha, Andrew W. Senior, Jonathan H. Connell, “Guide to Biometrics”,Springer 2013 (Unit 1)
2. Rafael C. Gonzalez, Richard Eugene Woods, “Digital Image Processing using MATLAB”, 2nd Edition, Tata McGraw-Hill Education 2010 (Unit 2)
3. Claus Vielhauer, “Biometric user authentication for IT security: from fundamentals to handwriting”, Vol. 18. Springer Science & Business Media, 2005 (Unit 2)
4. Anil Jain, Patrick Flynn, and Arun A. Ross, eds. “Handbook of biometrics”, Springer Science & Business Media, 2007 (Unit 3 & 4)
5. Richard O. Duda, David G.Stork, Peter E. Hart, “Pattern Classification”, Wiley 2007
6. Julian Ashbourn, “Biometrics in the New World”, Springer 2014.
7. Zhang, David, Lu, Guangming,“3D Biometrics Systems and Applications”, Springer 2013. (Unit 5)