Abstract
<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Biometric technology has attracted much attention in biometric recognition. Significant online and offline applications satisfy security and human identification based on this technology. Biometric technology identifies a human based on unique features possessed by a person. Biometric features may be physiological or behavioral. A physiological feature is based on the direct measurement of a part of the human body such as a fingerprint, face, iris, blood vessel pattern at the back of the eye, vascular patterns, DNA, and hand or palm scan recognition. A behavioral feature is based on data derived from an action performed by the user. Thus, this feature measures the characteristics of the human body such as signature/handwriting, gait, voice, gesture, and keystroke dynamics. A biometric system is performed as follows: acquisition, comparison, feature extraction, and matching. The most important step is feature extraction, which determines the performance of human identification. Different methods are used for extraction, namely, appearance- and geometry-based methods. This paper reports on a review of human identification based on geometric feature extraction using several biometric systems available. We compared the different biometrics in biometric technology based on the geometric features extracted in different studies. Several biometric approaches have more geometric features, such as hand, gait, face, fingerprint, and signature features, compared with other biometric technology. Thus, geometry-based method with different biometrics can be applied simply and efficiently. The eye region extracted from the face is mainly used in face recognition. In addition, the extracted eye region has more details as the iris features.</span>
Highlights
The term biometric is derived from the Greek words bio, which means “life,” and metric, which means “the measure of.” Biometrics is the automated use of unique and measurable characteristics to establish or verify an identity based on some special biometric features derived from physiological and behavioral characteristics (Tiwari, Chourasia, & Chourasia, 2015; Jayaram & Fleyeh, 2013; Mäkinen & Raisamo, 2008; Vaidya, 2015).verification and identification are interchangeably used in the literature for biometric recognition (Mir, Rubab, & Jhat, 2011)
Biometric technologies have recently played an important function as a suitable method of identification
We focus in geometry features extraction techniques, the most important issues in these techniques are the emphases in the choosing a appropriate geometry features that can identification human being, where this can be achieved by conducted several experiments with different geometry features
Summary
The term biometric is derived from the Greek words bio, which means “life,” and metric, which means “the measure of.” Biometrics is the automated use of unique and measurable characteristics to establish or verify an identity based on some special biometric features derived from physiological and behavioral characteristics (Tiwari, Chourasia, & Chourasia, 2015; Jayaram & Fleyeh, 2013; Mäkinen & Raisamo, 2008; Vaidya, 2015). (Erno et al, 2008) found that biometrics can enhance the high assurance to a system, when tied with one or two other forms of verification These “multimodal” forms of authentication (e.g., passwords together with speech, speech together with gesture, or passwords together with speech and eye features) allow the potential for significant state of security and privacy enhancement. Biometrics requires much data of an individual to be stored These systems are not always reliable because a person changes over time, such as when the eyes turn puffy or when the voice of a person changes when the person is ill. This paper represents a review of human identification based on geometric feature extraction using several biometric systems available, after-study papers, articles, conference paper, and from our experiments in previous works in this field.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
