Biometric Face Recognition Research Paper

Fig. 2: Hand Geometry

3.4 Iris

The iris is a circular, thin structure in the eye, which is responsible for controlling the diameter and size of the pupil. This way it controls the amount of light reaching the retina. The visual texture of the iris is formed during the first two years of life. Each iris is distinctive and, like fingerprints, even the irises of identical twins are different.

Iris recognition algorithms can identify about 200 identification points including the ring. Localize inner and outer boundary of the iris in an image of an eye. Then it detects and excludes the eyelid, eyelashes, and this kind of specular reflections which are not the part of inner eye. Take a set of pixels that contains only the iris. Pupil dilation and

The variation in face or unique features of the face such as distance between eyes, nose, mouths, ears, jaw, size of eyes, mouth and others expressions etc. helps us to uniquely identify each people individually. This uniqueness of our face is the key behind one of the most useful and reliable biometric security system face recognition.

Biometric Face recognition technique works in several stages, first face is detected in a picture or image frame, then unique feature of that face is extracted and stored in database, later a face classifier is trained with those features to identify each individual, finally we use that trained classifier to identify any given face.

Face recognition has several advantages over other biometric systems (fingerprint/iris) due to its non-contact process. Face recognition is more flexible and less costly as a person can be identified just using a facial image of that person without touching or interacting with the person. Due to its wide range of application such as biometric security, behavioral analysis, authentication etc. face recognition has gain a great research interest and commercial

5: Voice Recognition

3.7 Gait

Gait recognition is a technique by which a person’s biometric information can be identified by analyzing the way of walking or any other action which has cyclic combination and temporal pattern. Observing the walk of a human being has an interesting topic for the psychologists for a long time. But recently the machine reading enhance the recognition efficiency of some biometric information such as identity, gender, age, physical health conditions, psychological conditions etc.

The gait recognition technique is mainly based on extracting series images from video sample and analyzed it via a mathematical model. The key issues of recognitions are to find cyclic motions, from there the oscillating signals with its frequency, phase angles etc. can be identified which can further translate into features which is dynamic. Some identified features can be the trajectories of the main joints and angle of human body. After getting the features it can easily compare with features database to identify specific issues. The whole process can be done by taking videos by camera or by radar system. Fig. 6: Basic block diagram of gait recognition