EE435 – BIOMETRIC SIGNAL PROCESSING

Description

This course is an introduction to the means and methods to automatically identify people based on their unique physical or physiological traits, called biometrics. It provides an overview of pattern recognition and image processing techniques, then covers how to apply those methods to the identification of irises, faces, fingerprints, and hand geometry.

Prereq: EE353 and EE322, or Department Chair approval.

Course Objectives:

1. Discuss the various methods available for personnel identification, including things you know, things you have, and your physical or behavioral traits. State the advantages and disadvantages of each.
2. Describe the processes of biometric enrollment, identification and verification.
3. Explain the common performance metrics for biometric identification, including FAR, FRR and ROC curves. Define the terms “imposter” and “genuine” as they apply to performance.
4. Apply image processing techniques to digital imagery using MATLAB, Python or C++ in order to preprocess an image, extract features, and perform matching for identification or verification.
5. Use commercial biometric systems for enrollment, identification and verification

Spring 2020 Section 1121