Intelligent Biometric Techniques In Fingerprint And Face Recognition Pdf
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- Handbook of Fingerprint Recognition
- Facial recognition system
- Video-based facial recognition - Thales Facial Recognition Platform
- SpeedFace-V5L [TD]
The four coauthors have a distinguished combination of academic and professional experience Overall, readers will be pleased with the style and substance of this book.
It supports both facial and palm verification with large capacity and speedy recognition, as well as improves security performance in all aspects. It is also equipped with ultimate anti-spoofing algorithm for facial recognition against almost all types of fake photos and videos attack. The terminal with body temperature measurement and mask detection SpeedFace-V5L [TD] will be a perfect choice to help reduce the spread of germs and prevent infections straightly at each access point of any premises and public areas such as hospitals, factories, schools, commercial buildings, stations during the outbreak of infectious and contagious diseases with its fast and accurate body temperature measurement and masked individual identification funtions during facial and palm verification. Skip to main content.
Handbook of Fingerprint Recognition
Biometrics are body measurements and calculations related to human characteristics. Biometrics authentication or realistic authentication is used in computer science as a form of identification and access control.
It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Biometric identifiers are often categorized as physiological versus behavioral characteristics. Physiological characteristics are related to the shape of the body. Behavioral characteristics are related to the pattern of behavior of a person, including but not limited to typing rhythm , gait , keystroke , signature , behavioral profiling, and voice.
Some researchers have coined the term behaviometrics to describe the latter class of biometrics. More traditional means of access control include token-based identification systems , such as a driver's license or passport , and knowledge-based identification systems, such as a password or personal identification number. Since biometric identifiers are unique to individuals, they are more reliable in verifying identity than token and knowledge-based methods; however, the collection of biometric identifiers raises privacy concerns about the ultimate use of this information.
Many different aspects of human physiology, chemistry or behavior can be used for biometric authentication. The selection of a particular biometric for use in a specific application involves a weighting of several factors.
Jain et al. Proper biometric use is very application dependent. Certain biometrics will be better than others based on the required levels of convenience and security. The block diagram illustrates the two basic modes of a biometric system. Three steps are involved in the verification of a person. In the second step, some samples are matched with reference models to generate the genuine and impostor scores and calculate the threshold. The third step is the testing step.
This process may use a smart card , username or ID number e. PIN to indicate which template should be used for comparison. Second, in identification mode the system performs a one-to-many comparison against a biometric database in an attempt to establish the identity of an unknown individual. The system will succeed in identifying the individual if the comparison of the biometric sample to a template in the database falls within a previously set threshold.
Identification mode can be used either for 'positive recognition' so that the user does not have to provide any information about the template to be used or for 'negative recognition' of the person "where the system establishes whether the person is who she implicitly or explicitly denies to be".
The first time an individual uses a biometric system is called enrollment. During enrollment, biometric information from an individual is captured and stored. In subsequent uses, biometric information is detected and compared with the information stored at the time of enrollment.
Note that it is crucial that storage and retrieval of such systems themselves be secure if the biometric system is to be robust. The first block sensor is the interface between the real world and the system; it has to acquire all the necessary data. Most of the times it is an image acquisition system, but it can change according to the characteristics desired. The second block performs all the necessary pre-processing: it has to remove artifacts from the sensor, to enhance the input e.
In the third block, necessary features are extracted. This step is an important step as the correct features need to be extracted in an optimal way. A vector of numbers or an image with particular properties is used to create a template. A template is a synthesis of the relevant characteristics extracted from the source. Elements of the biometric measurement that are not used in the comparison algorithm are discarded in the template to reduce the filesize and to protect the identity of the enrollee.
During the enrollment phase, the template is simply stored somewhere on a card or within a database or both. During the matching phase, the obtained template is passed to a matcher that compares it with other existing templates, estimating the distance between them using any algorithm e.
Hamming distance. The matching program will analyze the template with the input. This will then be output for a specified use or purpose e. The selection of a biometric is based on user requirements and considers sensor and device availability, computational time and reliability, cost, sensor size, and power consumption.
Multimodal biometric systems use multiple sensors or biometrics to overcome the limitations of unimodal biometric systems. While unimodal biometric systems are limited by the integrity of their identifier, it is unlikely that several unimodal systems will suffer from identical limitations.
Multimodal biometric systems can obtain sets of information from the same marker i. Multimodal biometric systems can fuse these unimodal systems sequentially, simultaneously, a combination thereof, or in series, which refer to sequential, parallel, hierarchical and serial integration modes, respectively.
Fusion of the biometrics information can occur at different stages of a recognition system. In case of feature level fusion, the data itself or the features extracted from multiple biometrics are fused. Matching-score level fusion consolidates the scores generated by multiple classifiers pertaining to different modalities. Finally, in case of decision level fusion the final results of multiple classifiers are combined via techniques such as majority voting.
Feature level fusion is believed to be more effective than the other levels of fusion because the feature set contains richer information about the input biometric data than the matching score or the output decision of a classifier. Therefore, fusion at the feature level is expected to provide better recognition results.
Spoof attacks consist in submitting fake biometric traits to biometric systems, and are a major threat that can curtail their security. Multi-modal biometric systems are commonly believed to be intrinsically more robust to spoof attacks, but recent studies  have shown that they can be evaded by spoofing even a single biometric trait.
The discriminating powers of all biometric technologies depend on the amount of entropy they are able to encode and use in matching. An early cataloguing of fingerprints dates back to when Juan Vucetich started a collection of fingerprints of criminals in Argentina. Adaptive biometric systems aim to auto-update the templates or model to the intra-class variation of the operational data.
Recently, adaptive biometrics have received a significant attention from the research community. This research direction is expected to gain momentum because of their key promulgated advantages.
First, with an adaptive biometric system, one no longer needs to collect a large number of biometric samples during the enrollment process. Second, it is no longer necessary to enrol again or retrain the system from scratch in order to cope with the changing environment.
This convenience can significantly reduce the cost of maintaining a biometric system. Despite these advantages, there are several open issues involved with these systems. For mis-classification error false acceptance by the biometric system, cause adaptation using impostor sample.
However, continuous research efforts are directed to resolve the open issues associated to the field of adaptive biometrics. More information about adaptive biometric systems can be found in the critical review by Rattani et al.
In recent times, biometrics based on brain electroencephalogram and heart electrocardiogram signals have emerged. The advantage of such 'futuristic' technology is that it is more fraud resistant compared to conventional biometrics like fingerprints. However, such technology is generally more cumbersome and still has issues such as lower accuracy and poor reproducibility over time. This new generation of biometrical systems is called biometrics of intent and it aims to scan intent. The technology will analyze physiological features such as eye movement, body temperature, breathing etc.
On the portability side of biometric products, more and more vendors are embracing significantly miniaturized biometric authentication systems BAS thereby driving elaborate cost savings, especially for large-scale deployments. An operator signature is a biometric mode where the manner in which a person using a device or complex system is recorded as a verification template.
National Intelligence , and Senior Vice President of Booz Allen Hamilton promoted the development of a future capability to require biometric authentication to access certain public networks in his keynote speech  at the Biometric Consortium Conference.
A basic premise in the above proposal is that the person that has uniquely authenticated themselves using biometrics with the computer is in fact also the agent performing potentially malicious actions from that computer.
However, if control of the computer has been subverted, for example in which the computer is part of a botnet controlled by a hacker, then knowledge of the identity of the user at the terminal does not materially improve network security or aid law enforcement activities.
Recently, another approach to biometric security was developed, this method scans the entire body of prospects to guarantee a better identification of this prospect. This method is not globally accepted because it is very complex and prospects are concerned about their privacy.
Rather than tags or tattoos, biometric techniques may be used to identify individual animals : zebra stripes, blood vessel patterns in rodent ears, muzzle prints, bat wing patterns, primate facial recognition and koala spots have all been tried.
Videos have become a pronounced way of identifying information. There are features in videos that look at how intense certain parts of a frame are compared to others which help with identification. Biometrics are employed by many aid programs in times of crisis in order to prevent fraud and ensure that resources are properly available to those in need. Humanitarian efforts are motivated by promoting the welfare of individuals in need, however the use of biometrics as a form of surveillance humanitarianism can create conflict due to varying interests of the groups involved in the particular situation.
Disputes over the use of biometrics between aid programs and party officials stalls the distribution of resources to people that need help the most. In July , the United Nations World Food Program and Houthi Rebels were involved in a large dispute over the use of biometrics to ensure resources are provided to the hundreds of thousands of civilians in Yemen whose lives are threatened. The refusal to cooperate with the interests of the United Nations World Food Program resulted in the suspension of food aid to the Yemen population.
The use of biometrics may provide aid programs with valuable information, however its potential solutions may not be best suited for chaotic times of crisis. Conflicts that are caused by deep-rooted political problems, in which the implementation of biometrics may not provide a long-term solution.
Biometrics have been considered also instrumental to the development of state authority  to put it in Foucauldian terms, of discipline and biopower . By turning the human subject into a collection of biometric parameters, biometrics would dehumanize the person,  infringe bodily integrity, and, ultimately, offend human dignity. Agamben argued that gathering of biometric data is a form of bio-political tattooing, akin to the tattooing of Jews during the Holocaust.
According to Agamben, biometrics turn the human persona into a bare body. Agamben refers to the two words used by Ancient Greeks for indicating "life", zoe , which is the life common to animals and humans, just life; and bios , which is life in the human context, with meanings and purposes.
Agamben envisages the reduction to bare bodies for the whole humanity. The stark expansion of biometric technologies in both the public and private sector magnifies this concern. The increasing commodification of biometrics by the private sector adds to this danger of loss of human value. Indeed, corporations value the biometric characteristics more than the individuals value them.
Other scholars  have emphasized, however, that the globalized world is confronted with a huge mass of people with weak or absent civil identities. Most developing countries have weak and unreliable documents and the poorer people in these countries do not have even those unreliable documents.
Facial recognition system
The development of biometric applications, such as facial recognition FR , has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and methods for these types of systems and their applications in everyday life. FR is developing technology with multiple real-time applications. The goal of this paper is to develop a complete FR system using transfer learning in fog computing and cloud computing. The developed system uses deep convolutional neural networks DCNN because of the dominant representation; there are some conditions including occlusions, expressions, illuminations, and pose, which can affect the deep FR performance. DCNN is used to extract relevant facial features. These features allow us to compare faces between them in an efficient way.
Biometrics are body measurements and calculations related to human characteristics. Biometrics authentication or realistic authentication is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Biometric identifiers are often categorized as physiological versus behavioral characteristics. Physiological characteristics are related to the shape of the body. Behavioral characteristics are related to the pattern of behavior of a person, including but not limited to typing rhythm , gait , keystroke , signature , behavioral profiling, and voice.
Video-based facial recognition - Thales Facial Recognition Platform
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Its world-class algorithm based on deep neural networks ensures efficiency and accuracy for face detection, tracking, and recognition. FRP can process videos in both live or replay to identify people in a non-intrusive way, without any operator intervention. This module is designed to enhance the efficiency of security operations, by identifying 'persons of interest' in real-time video streams coming from a video management system.
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Ее руки спускались все ниже, забираясь под полотенце. Нуматака почти ничего не замечал. Мысли его были .
Острая боль обожгла грудь Беккера и ударила в мозг. Пальцы у него онемели. Он упал.
Он подумал, дома ли Сьюзан. Куда она могла уйти. Неужели уехала без меня в Стоун-Мэнор. - Эй! - услышал он за спиной сердитый женский голос и чуть не подпрыгнул от неожиданности.
Сьюзан огляделась. Третий узел был пуст, свет шел от работающих мониторов. Их синеватое свечение придавало находящимся предметам какую-то призрачную расплывчатость. Она повернулась к Стратмору, оставшемуся за дверью. В этом освещении его лицо казалось мертвенно-бледным, безжизненным. - Сьюзан, - сказал .
marianaslibrary.org Overview of Biometric and Facial Recognition Techniques Fingerprint recognition systems utilize the ability of the biometric device to and 'smart' national ID cards containing the index fingerprints and facial.
Если ТРАНСТЕКСТ до сих пор не дал ответа, значит, пароль насчитывает не менее десяти миллиардов знаков. Полнейшее безумие. - Это невозможно! - воскликнула она .
На его лекциях по этимологии яблоку негде было упасть, и он всегда надолго задерживался в аудитории, отвечая на нескончаемые вопросы. Он говорил авторитетно и увлеченно, не обращая внимания на восторженные взгляды студенток. Беккер был смуглым моложавым мужчиной тридцати пяти лет, крепкого сложения, с проницательным взглядом зеленых глаз и потрясающим чувством юмором. Волевой подбородок и правильные черты его лица казались Сьюзан высеченными из мрамора. При росте более ста восьмидесяти сантиметров он передвигался по корту куда быстрее университетских коллег.