**2. Person identification approaches (traditional vs. biometrics)**

The traditional human identification approaches depend on changeable parameters such as passwords or magnetic/ID cards. These parameters can be easily used by illegal persons, if they know the password or have the card. Losing, forgetting, or stealing are common disadvantages for all the traditional identification methods which make it unreliable and inaccurate especially in the high precise system such as forensics, financial, bank, and border ports systems. The need for more robust systems of person identification in addition to the development of the sensors and automated systems was incentive to construct the systems that depend on the unique features of each person. These features are extracted from a human trait such as fingerprint, face, and speech. Human recognition using features that are extracted from inherent physical or behavioral traits of the individuals is defined as biometrics. In addition to the enhancement of the efficiency and capability of recognition systems, biometrics facilitates identifying, and claiming process, where it is not required to memorize any passwords or to carry any ID cards such as passports or driving license.

Biometrics is the science of establishing the identity of an individual based on a vector of features derived from a behavioral characteristics or specific physical attribute that the person holds. The behavioral characteristic includes how the person interacts and moves, such as their speaking style, hand gestures, signature, etc. The physiological category includes the physical human traits such as fingerprints, iris, face, veins, eyes, hand shape, palmprint, and many more. Evaluating these traits assists the recognition process using the biometric systems [1].

A biometric system includes two main phases as enrollment and recognition. Biometric data (image, video, or speech) are captured and stored in a database in enrollment phase. The recognition phase mainly includes extraction of the salient features and generation of the matching scores in order to compare query features against the stored templates. The biometric system will report an identity at the end of the decision process after performing matching, and this will be the identity of the most resembling person in the database.
