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7BiOMETRiC RECOGNiTiON: AN ANALYSiS OF PERSON IDE NTiFiCATiON
AND METHODS
AGAMALiYEVA JEYRAN AGAMALi
Department of Computer Engineering, PhD in Technology, Lecturer, Azerbaijan Azerbaijan state university of oil and industry
HEYDAROVA RANA YUSiF
Department of Computer Engineering, Master, Azerbaijan Azerbaijan state university of oil and industry
Abstract. Biometric recognition systems provide personal identification of people by measuring and analyzing their physical and behavioral characteristics. In this article, basic biometric methods such as fingerprint recognition, face recognition, retina analysis, and voice recognition are analyzed. The advantages and disadvantages, application areas, and potential limitations of each method are also discussed. In addition, the facilities used to evaluate the performance of biometric recognition systems and the analysis of the use of these technologies in Azerbaijan are also conducted. The article highlights the importance of biometric recognition systems in the identification process and provides theoretical and empirical information on how these technologies can be used more effectively.
Keywords. Biometrics, person identification, biometric recognition, fingerprint recognition, face recognition, retina recognition, voice recognition, biometric methods.
Introduction. In recent years, biometric recognition systems have gained great interest due to their advanced capabilities in identifying individuals based on their unique physical and behavioral characteristics. These systems play a critical role in many application areas, from security access control to personal device authentication. Using biometric features such as fingerprint patterns, facial features, retinal structures, and voice patterns, these systems offer secure and convenient ways of authentication. This article presents a detailed analysis and comparison of biometric recognition methods for personal identification. The basic principles and operating mechanisms of each method are discussed in detail among the main biometric methods such as fingerprint recognition, face recognition, retina recognition and voice recognition. Advantages and disadvantages, areas of application, and potential limitations of each method are discussed. Through this article, we will try to highlight the importance of biometric identification systems in increasing security, solving authentication processes efficiently and ensuring user privacy.
Biometric Recognition Methods
Fingerprint recognition is one of the most widespread and effective methods of biometric recognition systems. This method follows the principle of recording the features of the distal (tip) section of a person's finger and storing it in digital form. Human fingerprints are identified based on unique features in the distal part of the fingers.
Fingerprint recognition is a complex process consisting of several main steps. In this step, an individual's fingerprint is entered into the system and scanned by the system to record the fingerprint's unique features, such as points and distances between them. This information is then stored in a person's database. After scanning, the recorded fingerprint data is digitally encrypted. This encryption process ensures that the fingerprint is stored in as compact and convenient a form as possible. In the identification phase, all fingerprints stored in the system's database are compared and a match is confirmed.
Face recognition is one of the most important methods of biometric recognition systems. This method performs identity verification by obtaining the unique features of a person's face. Each person's face has many different features, such as the shape of the eyes, the shape of the nose, the structure of the mouth and jaw [1]. Therefore, a facial recognition system can distinguish and recognize individuals using these features.
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The face recognition process is created through several stages. The first step is to recognize a person's face through a camera or sensor. This image will be recorded in digital form to be processed and analyzed by a facial recognition algorithm. The image is processed by a face recognition algorithm and features that are unique to the face are extracted. These features include features such as the distance between certain points of the face, the size and position of the eyes, and the shape of the nose. The extracted features are compared with the features of other faces registered in the database. This comparison process usually results in a match score or similarity score. The values obtained as a result of the comparison are compared with a certain equal value. Faces exceeding the equal value are taken into the verification process, and faces below the equal value are taken into the recognition process. While authentication provides verification of a person's identity, recognition is used to recognize a person we already know.
Retina recognition is one of the effective and reliable methods of biometric recognition systems [3]. This method performs identity verification using unique features in the retina of a person's eye. Each person's retina has a unique imprint made up of a combination of the retina's circumference, vessels, and other features.
The process of recognizing the retina of the eye generally consists of several processes. The first step is to image a person's retina through a camera or sensor. This image is recorded in digital form to be processed and analyzed by a retinal recognition algorithm. These features include lines in the shape of the retina, the arrangement of blood vessels, and other limitations. The extracted features are compared with retinal features of other eyes registered in the database. This comparison process usually results in a match value or similarity value.
Voice recognition is another important method of biometric recognition systems. This method uses a person's voice to identify the person. Each person's voice has a unique ability that is determined by its tone, frequency and other characteristics.
The process of voice recognition mainly consists of several steps. The first step is to receive a person's voice through a microphone or sound sensor. This sound is recorded in digital form to be processed and analyzed by a voice recognition algorithm. These features include pitch, tempo, emphasis, and other sound characteristics. The extracted features are compared with the features of other sounds registered in the database. This comparison process usually results in a match value or similarity value.
Additionally, biometric recognition technologies include methods such as DNA, hand geometry, skin electrophoresis, and gait analysis. DNA makes up the genetic code of humans, and each individual has different DNA characteristics [6]. DNA recognition works by reading and comparing this genetic information. Hand geometry uses parameters such as a person's hand shape, hand length and distance between fingers. Skin electrocardiography records electrocardiographic signals through an electrocardiographic sensor placed on a person's skin. Each person's skin electrophoresis functions as a unique signature based on their skin structure and natural electrical properties. Walking of people is also considered as a unique feature. Gait analysis uses a person's walking speed, step length, step coordination and other parameters. Choosing the optimal biometric recognition system should match the goals and requirements of the application.
Advantages and Disadvantages of Biometric Recognition Technologies
Fingerprint recognition systems work with full accuracy and false positive or false negative results are minimal. It is easy and convenient for users. The recognition process, a fingerprint passes through the sensor, and this to facilitate daily use and application. Fingerprint recognition systems can recognize several watches the same, so they can be widely used in every field of application. Some people can get fingerprints from skin injuries or other physical symptoms. This can affect the recognition process and reduce accuracy. Accurate fingerprint analysis requires full resolution sensors. low resolution or unacceptable sensor materials may reduce accuracy. Mobile phones, tablets and other mobile devices are one of the wide application areas of fingerprint biometrics. You can access users' devices with fingerprints, analyze their data. In the workplace or other organizations, fingerprint biometrics are widely used in the implementation of control systems. This is used to
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control entry and exits and track employee activities I believe. Fingerprint biometrics are widely used in institutions such as banks, healthcare facilities, and institutions.
Facial biometrics uses natural features of a person, so it is easy for users to recognize and use. Users can also use it on any device, such as a smartphone or computer, through facial recognition technology. This provides additional convenience along with its advantages. Face recognition minimizes restrictions and allows recognition without movement, which increases the convenience of use. In some cases, if the sensor or storage is not protected first, the system may be compromised. Factors such as aging, serious injuries, or plastic surgery procedures can cause facial changes. This can affect the recognition process and reduce accuracy. Accurate face recognition requires high-quality sensors. Poor quality or unacceptable sensor materials can reduce accuracy. Cell phones, tablets and other mobile devices are one of the common application areas of facial biometrics [4]. Users can access their devices with facial recognition and analyze their data. In the workplace or other organizations, facial recognition biometrics are widely used in implementing surveillance systems. Facial biometrics are widely used in security applications such as banks, healthcare facilities and institutions. This provides an additional level of security for data analysis and responsible use of products.
Retina recognition works at a fast and high-precision level, increasing the meaning of use. Retina does not require the user to apply, that is, the user can enter the system without applying in advance and without requiring any additional procedures. In some exceptional cases, the retina may experience limitations as a result of the diagnostic process, retinal changes or changes. As major security reports do not support retinal biometrics, some security manufacturers may not participate in using this technology. Banks, healthcare facilities, airports, and other high-security applications make extensive use of retinal biometrics. Retinal biometrics are used in healthcare settings, especially to analyze drug and prescription information [9]. City and public utility companies use retinal biometrics for monitoring and management purposes. High security devices and applications enable the use of retinal biometrics on mobile devices.
Voice biometrics is based on detailed measurements of people's voices. This allows users to be recognized independently of different text and language forms. Sound criticism is a natural process for humans. Voice biometrics uses people's voices in a natural way, so they are easy to recognize. Voice biometrics are quickly and easily digitized and processed. This increases the speed and efficiency of the recognition process. Voice biometrics has fewer limitations than other biometric methods because it uses the unique properties of voices. In some cases, there is a risk of audio data being intercepted by third parties. Aging, the flu, or other factors that affect the voice can cause voice changes. This can affect the recognition process and reduce accuracy. For voice biometrics to work properly, it is important that background noise is kept to a minimum. In some application areas, such as outdoor or noisy environments, this disadvantage arises. Voice biometrics are ideal for use in telecommunications [5]. Phone calls, web conferencing, and various audio platforms are examples of voice biometrics applications. Voice biometrics are used for city security, airport security and other reports. This makes voice biometrics an ideal choice for security reporting. Voice biometrics is also used in healthcare and medicine. Doctors provide medical services using voice biometrics for monitoring and authentication purposes.
Performance Evaluation Metrics
Accuracy rates, error rates, sensitivity and specificity are some of the fundamental criteria for evaluating the performance of biometric recognition systems [7]. These metrics help measure the accuracy and effectiveness of the results set by a system.
• Accuracy rates are used to measure the accuracy of the results generated by a biometric system. A high degree of accuracy indicates that the results organized by the system are correct and accurate.
• Error rates are used to measure the level of error in the results generated by a biometric system. This includes false positive and false negative rates.
• Sensitivity determines the percentage of objects or data correctly recognized by a biometric system. High sensitivity indicates a high percentage of objects or data correctly recognized by the
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system.
• Specificity defines the percentage of objects or data that are incorrectly recognized by a biometric system. High specificity indicates the minimum percentage of objects or data that are incorrectly recognized by the system.
These metrics form a solid basis for evaluating and comparing the effectiveness of a biometric recognition system [8]. Accuracy rates and error rates consider the accuracy and efficiency of the system, while sensitivity and specificity measure the percentage of objects or data correctly and incorrectly recognized by the system. These metrics provide important information for determining the performance and limitations of systems.
Processing speed and data security are one of the fundamental criteria for evaluating the effectiveness of biometric recognition systems and the reliability of users' data [2]. These two factors are critical in ensuring the performance of systems and the security of users' data.
1. Processing speed measures how fast a biometric recognition system is in the process of receiving, analyzing and determining the result. High processing speed allows systems to be more efficient and provide a more comfortable experience for users.
2. Data security assesses how biometric recognition systems protect users' data and create a secure environment. This includes the secure storage, use and other security procedures of users' biometric data.
3. Biometric recognition systems protect data through encryption and other security protocols. A high degree of encryption and data protection helps ensure the privacy and security of users' data.
4. Biometric recognition systems are responsible for storing and using users' biometric data. Properly storing this data and using it only for secure purposes ensures data security.
5. The sharing and use of biometric data must ensure that the data complies with legal and identity protection standards and implement secure procedures that protect the privacy of users' data.
These criteria constitute a fundamental framework for evaluating the performance of biometric recognition systems and the security of users' data. Processing speed and data security are critical in measuring the power of a system and its effectiveness in securing users' data.
Use of Biometric Recognition Technologies in Azerbaijan
The historical development of biometric recognition systems in Azerbaijan has been progressing rapidly in recent years. These systems use different physical characteristics to analyze recognition data and identify people. The historical development of biometric recognition systems begins with fingerprint recognition systems, which itself is one of the first examples. Fingerprint recognition systems are among the widely used systems in Azerbaijan. These systems are widely used to identify passengers and other individuals by fingerprint tradition and legislation. Also, the use of voice and face recognition systems has been widespread in Azerbaijan in recent years. These systems, combined with other biometric methods, provide more effective use.
Biometric recognition systems are used in the healthcare and medical fields, for example, to provide identification to patients or medical personnel. These systems are used to analyze patients' health records, automatically record prescriptions and medical orders, and analyze related data. In the field of education, biometric recognition systems are used for identification purposes for schools and universities. These systems are used to manage the entry and exit of students and cultural workers, and to automate and monitor testing and certification work. Biometric recognition systems are used for identification purposes at border checkpoints and airports. These systems assist in identifying passengers for travel purposes, verifying passport information and identifying potentially dangerous individuals. In the military field, biometric recognition systems are used for identification of military personnel, data acquisition, and fast and secure access to military bases. In the banking and financial sector, biometric recognition systems are used to verify the identity of bank customers and ensure the security of banking transactions. In these areas, the use of biometric recognition systems is common, both with the aim of automating processes and increasing security. It is expected that these systems
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will spread more widely and increase the areas of use in Azerbaijan.
Legal challenges and ethical issues have been a source of increasing interest with the development of biometric recognition systems. The use of these systems raises many legal and ethical questions and requires compliance with existing legislation and ethical standards:
• Biometric recognition systems use personal information such as fingerprints, faces, voice signals and other biometric data to record. This raises privacy and data security issues related to the storage, processing and protection of personal data.
• Biometric data can also be used for nefarious purposes by third parties without users' consent. This raises serious ethical issues regarding the protection of users' data and identity protection.
• Laws and regulations regarding the use of biometric recognition systems are still evolving. This raises questions such as how use is legally regulated and how users' privacy rights are protected.
These issues are at the center of the global debate on the use of biometric recognition systems and require serious care and security measures. Legal challenges and ethical issues must be continually evaluated to manage the development and use of these systems.
CONCLUSiON
Based on the research, topics such as the effectiveness of various biometric methods, privacy issues, performance metrics, legal challenges, and ethical issues were discussed in detail. The obtained results clearly show the strengths and weaknesses of biometric recognition systems. In order to increase efficiency and ensure privacy, it is emphasized that these systems need a deeper development and improvement. Also, it is important that these systems are better monitored within legal challenges and ethical issues. In the future, biometric recognition systems will be further developed by combining with other technologies. Combining different biometric methods, such as voice, face, and retina recognition, will allow the development of more secure and effective recognition systems. Also, more emphasis is expected on important factors such as speed, data security, and depth of defenses. This will create conditions for the development of more complex biometric recognition systems and enable these systems to be applied more effectively in various fields. In conclusion, biometric recognition systems are a constantly evolving technology in terms of security, efficiency and privacy. In the future, the further integration and development of these systems will make people's lives safer and more comfortable, and will create wider application opportunities in various fields.
Impact Factor: SJIF 2G21 - 5.S1 2G22 - 5.94
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