Week 3

Literature Review - More sources on visual recognition were reviewed in order to understand the techniques used in current facial recognition strategies such as using the 'eigenface' values. As visual recognition sources were finalized, voice analysis sources as well as fingerprint analysis sources started to be reviewed.

Signal Processing was discussed among group members to get everyone on track. How far the project could be taken based on current resources were discussed, such as the possibility of dropping one of the security measures in order to full master the other ones. Programming strategies were also discussed, such as the steps that need to be taken to identify people by their faces. The steps are as follows:

1.  Take pictures of the people doing different facil expressions and put them into a master database
2.  Upon initialization of the program, take picture of the user's face, who will line up with a template on the screen.
3. Use picture and compare it to the pictures in database
4. Output a final result of % match

Week 2 - Introduction

This week, the group designed the blog and decided on a topic: biometric recognition for control. This project makes use of biometric characteristics such as voice, facial features, and fingerprints to successfully identify an individual and cross-reference with an existing database of biometric templates.


The next step in the project will be to interface the webcam and microphone with MATLAB. Preliminary tests will be conducted and appropriate schematics will be uploaded.

Initial Research:

Biometric recognition is a rapidly-developing pattern recognition system used for a variety of purposes including verification, identification, and security as seen in Figure 1 [1]. Biometric recognition has applicability for individuals with restricted mobility such as those who cannot type or speak their password and acts as an additional safeguard for security purposes. Many biometric recognition systems “conduct a one-to-many comparison to establish an individual’s identity” [1]. It is also much more difficult for hackers and those with malicious intentions to forge or replicate biometric features. Many unique individual features can be used to distinguish one person from another such as fingerprints, facial features, irises, hand geometry, and even a person’s voice [1].

Figure 1. Sample biometric recognition flowchart for verification and identification of an individual.

The major tasks to be performed throughout the ten-week project are to develop a multi-faceted identification system that can cross-reference a person’s facial photograph and fingerprint with an existing database. There are inherent challenges when trying to accomplish this task, primarily due to the complexity of biometric features and the generation of a unique template for each individual. In the end, the desired result is to successfully identify, with minimum errors in identifying the wrong individual or failing to identify the proper individual, a person using multiple physiological characteristics.

            Developing a functional computer application capable of doing intensive image and signal processing requires significant prior experience with computer programming. Familiarity with MATLAB/Java is recommended for this project because of the well-written API and preexisting classes for processing external video and audio output. In addition, some knowledge of biomedical engineering is useful to understand which physiological features are unique amongst individuals. For example, it is important to know that features like fingerprints can be practically used to identify people while other features like the shape of the head may be too general for implementation. Some existing biometric technologies and their advantages and disadvantages are seen in Figure 2:

Figure 2. Pro-con analysis table of biometric technologies identifying various physiological features.

References

[1] A. K. Jain. (2007). “Biometric recognition.” Nature. [Online]. 449, pp. 38-40.

[2] S. Prabhakar. (2003, March). “Biometric recognition: Security and Privacy
Concerns.” IEEE Security and Privacy. [Online]. 1(2), pp. 33-42.