Facial recognition is one of the widely and most commonly used biometric application and this can also considered as the natural means of identification technique that were in the market. Any high quality camera with capability capture the images with a very high resolution can be used to capture the images of human faces and also a scanned copy of the image can also be used for this facial recognition process. More accurate results can be produced by the better image that is captured either by a camera or we can use scan copy. Gray-scale information is the primary input for facial recognition systems.
The colors of the final image captured are only taken in to consideration for identifying the face in the entire picture that was captured. Quality of the camera plays a very important role in the lightening conditions. A poor light condition does not make sense to identify an individual facial features and thus a proper steps need to be taken to avoid the poor camera light if there exists any thing. Now-a-days the most advanced infrared cameras can be used for these facial recognition systems.
For a better picture quality the desired user should be at a pre-defined distance from the particular camera, so that the facial recognition system can get an extra quality input for it’s internal processing. Locating the face with in the entire image would be the very first task of any facial recognition systems and the respective facial characteristics are captured. After locating the face in the image, the system focus on eyes of the face as shown in the below image
Facial metrics mainly depends on measurement of specific features of face like eyes, nose and mouth and also distance between them is also considered. Now-a-days a more sophisticated method for recognizing the face has been developed and widely used since three years. As per this method the faces are categorized based on the angle of fit and with a “fixed set of 150 master eigenfaces. In this process every face is assigned a degree of fit to each of the 150 master eigenfaces and only the 40 template eigenfaces with the highest degree of fit are necessary to reconstruct the face with the accuracy of 99%.”
A computer software will take care of the image processing and calculates the degree of fit. A lot of intelligent computing power is required to process this technique and assembling a stand alone face recognition system may not serve the purpose. There were lot of efforts now a days to build a sophisticated and chip based embedded system that can be used for facial recognition system which holds a special instruction set.
The accuracy of the computer software is not that ideal and has lot of disadvantages that can be discussed and still there is a lot of potential scope of improvising the algorithms being used as of now. The current software in place may not recognize the face or may identify the face at a wrong place. If the eyes are positioned at the exact place then much better results can be achieved.
The face recognition can be re-sizeable up to an extent like 150X100 points. This normalized shape of the face is called canonical image and the size of this template can be in the range of 3 to 5 KB and is as shown below
Retina scan can be considered as one of the important biometric scanning methodologies. This particular process of scanning the retina is mainly based on the vessel pattern of the blood that resides inside the retina of any eye. “The first retinal scanning systems were launched by EyeDentify in 1985”. Infra red light source influences the retina apart from the normal visualization. Blood vessels present inside the retina of eye absorbs the infrared radiations very quickly and the tissue is also affected by this absorption. The retina blood vessel pattern is captured as an image and special characteristic points are analyzed. Below image shows a typical retina patterns
Intrusiveness can be considered as the main drawback of the retina scanning process. The way the retina scan was obtained can be considered as not safe and is much dangerous when suggested. The cornea of eye is directly affected by the laser light during the retina scan and this process is not that easy to execute and requires a lot of skilled operations and instruction sequences. The volume of data produced by retinal scan is almost same as the fingerprint scan process and thus this scan process can be used both for identification and verification.
In the practice, however, the retina scanning is used mostly for verification. The size of the eye signature template is 96 bytes. Retina scan produces much more accurate results
Because of it’s less user friendliness and expensive retina scan is not being used widely and is used rarely. This retina scan can be launched and implement in cases where there is a huge scope for security and user authentication. Retina scan systems are used in many U.S. prisons to verify the prisoners before they are released. Below figure shows a typical retinal scanner system that was used commonly