Extraction & Recognition:

A normalized image can be processed further for feature extraction and recognition. Here, the images are converted to a mathematical representation, called biometric template or biometric reference, to store them into the database. These image database, then serves for verification and identification of probe images. This transformation of image data to mathematical representation is achieved through algorithms. Many Facial recognition algorithms have been developed to get simplified mathematical form, to carry out the task of recognition. The way the algorithms transform or translate the image data which is in form of gray scale pixels to the mathematical representation of features, differentiate them from one another. To retain maximum information in the transformation process and thus create a distinct biometric template is crucial for successful recognition. Failing to which, may cause problems like generation of biometric doubles i.e. the biometric templates from different individuals become insufficiently distinctive.