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Recent Advancements in Biometrics: Vein and Fingerprint Authentication
No full textBiometric signatures, or biometrics, are used to identify individuals by measuring certain unique physicaland behavioral characteristics. Individuals must be identified to allow or prohibit access to secure areas—or to enablethem to use personal digital devices such as, computer, personal digital assistant (PDA), or mobile phone. Virtually all biometric methods are implemented using the following 1) sensor, to acquire raw biometric data from an individual;
2) feature extraction, to process the acquired data to develop a feature-set that represents the biometric trait; 3) pattern matching, to compare the extracted feature-set against stored templates residing in a database; and 4) decisionmaking, whereby a user’s claimed identity is authenticated or rejected. In this paper, a compact system that consists of a CMOS fingerprint sensor (FPC1011F1) is used with the FPC2020 power efficient fingerprint processor ; which
acts as a biometric sub-system with a direct interface to the sensor as well as to an external flash memory for storing finger print templates. Distinct Area Detection (DAD) algorithm; which is a feature based algorithm is used by the fingerprint processor, which offer improvements in performance. Vein authentication is another recent advancement in
biometrics. Vein biometrics is discussed and comparison with other biometrics is revealed
Access control using fingerprint authentication processor and RFID
No full textA typical access control system uses two components. First component is a fingerprint reader that is connected to a database to match the pre stored fingerprints with the one obtained by the reader. The second component is an RFID card that transmits information about the person that requests an access. In this paper, a compact system that consists of a CMOS fingerprint sensor (FPC1011F1) is used with the FPC2020 power efficient fingerprint processor ; which acts as a biometric sub-system with a direct interface to the sensor as well as to an external flash memory for storing finger print templates. The small size and low power consumption enables this integrated device to fit in smaller portable and battery powered devices utilizing high performance identification speed. An RFID circuit is integrated with the sensor and fingerprint processor to create an electronic identification card (e-ID card). The e-ID card will pre-store the fingerprint of the authorized user. The RFID circuit is enabled to transmit data and allow access to the user, when the card is used and the fingerprint authentication is successful
Vein and Fingerprint Biometrics Authentication- Future Trends
No full textBiometric signatures, or biometrics, are used to identify individuals by measuring certain unique physical and behavioral characteristics. Individuals must be identified to allow or prohibit access to secure areas—or to enable them to use personal digital devices such
as, computer, personal digital assistant (PDA), or mobile phone. Virtually all biometric methods are implemented using the following 1) sensor, to acquire raw biometric data from an individual; 2) feature extraction, to process the acquired data to develop a feature-set that represents the biometric trait; 3) pattern matching, to compare the extracted feature-set against stored templates residing in a database; and 4) decision-making, whereby a user’s claimed identity is authenticated or rejected. In this paper, a compact system that consists of a CMOS fingerprint sensor (FPC1011F1) is used with the FPC2020 power efficient fingerprint processor ; which acts as a biometric sub-system with a direct interface to the sensor as well as to an external flash memory for storing finger print templates. Distinct Area Detection (DAD) algorithm; which is a feature based algorithm is used by the fingerprint processor, which offer improvements in performance. Vein authentication is another recentadvancement in biometrics. Vein biometrics is discussed and comparison with other biometrics is revealed
Vein and Fingerprint Biometrics Authentication- Future Trends
No full textBiometric signatures, or biometrics, are used to identify individuals by measuring certain unique physical and behavioral characteristics. Individuals must be identified to allow or prohibit access to secure areas—or to enable them to use personal digital devices such
as, computer, personal digital assistant (PDA), or mobile phone. Virtually all biometric methods are implemented using the following 1) sensor, to acquire raw biometric data from an individual; 2) feature extraction, to process the acquired data to develop a feature-set that represents the biometric trait; 3) pattern matching, to compare the extracted feature-set against stored templates residing in a database; and 4) decision-making, whereby a user’s claimed identity is authenticated or rejected. In this paper, a compact system that consists of a CMOS fingerprint sensor (FPC1011F1) is used with the FPC2020 power efficient fingerprint processor ; which acts as a biometric sub-system with a direct interface to the sensor as well as to an external flash memory for storing finger print templates. Distinct Area Detection (DAD) algorithm; which is a feature based algorithm is used by the fingerprint processor, which offer improvements in performance. Vein authentication is another recent advancement in biometrics. Vein biometrics is discussed and comparison with other biometrics is revealed
A potable biometric access device using dedicated fingerprint processor
No full textBiometric signatures, or biometrics, are used to identify individuals by measuring certain unique physical and behavioral characteristics. Individuals must be identified to allow or prohibit access to secure areas--or to enable them to use personal digital devices such as, computer, personal digital assistant (PDA), or mobile phone. Virtually all biometric methods are implemented using the following 1) sensor, to acquire raw biometric data from an individual; 2) feature extraction, to process the acquired data to develop a feature-set that represents the biometric trait; 3) pattern matching, to compare the extracted feature-set against stored templates residing in a database; and 4) decision-making, whereby a user's claimed identity is authenticated or rejected. A typical access control system uses two components. First component is a fingerprint reader that is connected to a database to match the pre stored fingerprints with the one obtained by the reader. The second component is an RFID card that transmits information about the person that requests an access. In this paper, a compact system that consists of a CMOS fingerprint sensor (FPC1011F1) is used with the FPC2020 power efficient fingerprint processor; which acts as a biometric sub-system with a direct interface to the sensor as well as to an external flash memory for storing finger print templates. The small size and low power consumption enables this integrated device to fit in smaller portable and battery powered devices utilizing high performance identification speed. An RFID circuit is integrated with the sensor and fingerprint processor to create an electronic identification card (e-ID card). The e-ID card will pre-store the fingerprint of the authorized user. The RFID circuit is enabled to transmit data and allow access to the user, when the card is used and the fingerprint authentication is successful
Steganalysis of JPEG images: an improved approach for breaking the F5 algorithm
No full textPeople often transmit digital images over the internet and JPEG is one of the most common used formats. Steganography is the art and science of hiding communication; the information hiding process thus uses an image as a cover medium to embed a hidden message. Steganalysis is the inverse process of trying to identify the existence of hidden message in a cover image. In this paper, we present an enhancement to the steganalysis algorithm that successfully attacks F5 steganographic algorithm. The key idea is related to the selection of an "optimal" value of β (the probability that a non-zero AC coefficient will be modified) for the image under consideration. Rather than averaging the values of β for 64 shifting steps worked on an image, an optimal β is determined that corresponds to the shift having minimal distance E from the double compression removal step. Numerical experiments were carried out to validate the proposed enhanced algorithm and compare it against the original one. Both algorithms were tested and compared using two sets of test images. The first set uses reference test data of 20 grayscale images [1], and the second uses 432 images created by manipulating 12 images for various image parameters: two sizes (300×400 and 150×2000), six JPEG old quality factors (50, 60, 70, 80, 90, 100), and 3 message lengths (0, 1kB, 2 kB). The results suggest that the original algorithm may be used as a classifier, since it shows a good detection performance of both clean and stego test images; whereas, the proposed enhanced algorithm may be used as an estimator for the true message length for those images that have been classified by original algorithm as stego images
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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