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18
Recent advances in biometric person authentication
- In: Proc. Internat. Conf. Acoustics, Speech Signal Processing
, 2002
"... Biometrics is an emerging topic in the field of signal processing. While enabling technologies (e.g. audio, video) for biometrics have mostly used separately, ultimately, biometric technologies could find their strongest role as interwined and complementary pieces of a multi-modal authentication sys ..."
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Biometrics is an emerging topic in the field of signal processing. While enabling technologies (e.g. audio, video) for biometrics have mostly used separately, ultimately, biometric technologies could find their strongest role as interwined and complementary pieces of a multi-modal authentication system. In this paper, a short overview of voice, fingerprint, and face authentication algorithms is provided. 1.
A probabilistic model of face mapping with local transformations and its application to person recognition
- IEEE TPAMI
, 2005
"... Abstract—This paper proposes a new measure of “distance ” between faces. This measure involves the estimation of the set of possible transformations between face images of the same person. The global transformation, which is assumed to be too complex for direct modeling, is approximated by a patchwo ..."
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Abstract—This paper proposes a new measure of “distance ” between faces. This measure involves the estimation of the set of possible transformations between face images of the same person. The global transformation, which is assumed to be too complex for direct modeling, is approximated by a patchwork of local transformations, under a constraint imposing consistency between neighboring local transformations. The proposed system of local transformations and neighboring constraints is embedded within the probabilistic framework of a two-dimensional hidden Markov model. More specifically, we model two types of intraclass variabilities involving variations in facial expressions and illumination, respectively. The performance of the resulting method is assessed on a large data set consisting of four face databases. In particular, it is shown to outperform a leading approach to face recognition, namely, the Bayesian intra/extrapersonal classifier. Index Terms—Biometrics, face recognition, image processing, hidden Markov model, distance. 1
Noisy Fingerprint Image Enhancement Technique for Image Analysis: A Structure Similarity Measure Approach
, 2007
"... Fingerprint images vary in quality. In order to ensure that the performance of an automatic fingerprint identification system (AFIS) will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement module in the AFIS system. In this pap ..."
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Fingerprint images vary in quality. In order to ensure that the performance of an automatic fingerprint identification system (AFIS) will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement module in the AFIS system. In this paper, we introduce a special domain fingerprint enhancement methods which decomposes the input fingerprint image into a set of filtered images. From the filtered images, the orientation field is estimated and a quality mask which distinguishes the recoverable and unrecoverable corrupted regions in the input image is generated. Using the estimated orientation field, the input fingerprint image is adaptively enhanced in the recoverable regions A technology for recognizing fingerprints for security purposes is proving as regards as reliable but efficient recognition is depending on the quality of input fingerprint image. Recognition of the fingerprint becomes a complex computer problem while dealing with noisy and low quality images. In this Paper work we are focusing the special domainn biometric System of noisy and low quality images, which will be beneficial for recognition system. Experimental results show that our enhancement Methods improves the performance of the fingerprint Images makes it more robust with respect to the quality of input.
Model-based Design for Selecting Fingerprint Recognition Algorithms for Embedded Systems
- in Proceedings of the 19th IEEE International Conference on Electronics, Circuits and Systems (ICECS
, 2012
"... Abstract-Most of contributions for biometric recognition solutions (and specifically for fingerprint recognition) are implemented in software on PC or similar platforms. However, the wide spread of embedded systems means that fingerprint embedded systems will be progressively demanded and, hence, h ..."
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Abstract-Most of contributions for biometric recognition solutions (and specifically for fingerprint recognition) are implemented in software on PC or similar platforms. However, the wide spread of embedded systems means that fingerprint embedded systems will be progressively demanded and, hence, hardware dedicated solutions are needed to satisfy their constraints. CAD tools from Matlab-Simulink ease hardware design for embedded systems because automatize the design process from high-level descriptions to device implementation. Verification of results is set at different abstraction levels (highlevel description, hardware code simulation, and device implementation). This paper shows how a design flow based on models facilitates the selection of algorithms for fingerprint embedded systems. In particular, the search of a solution for directional image extraction suitable for its application to singular point extraction is detailed. Implementation results in terms of area occupation and timing are presented for different Xilinx FPGAs.
An Investigation of Predictive Profiling from Handwritten Signature Data
- 10TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION
, 2009
"... Although it has long been recognised that non-biometric factors (for example, general demographic characteristics) can have an impact on the performance of automated person identification systems, such information is not routinely adopted in most practical biometric processing. In forensic applicati ..."
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Although it has long been recognised that non-biometric factors (for example, general demographic characteristics) can have an impact on the performance of automated person identification systems, such information is not routinely adopted in most practical biometric processing. In forensic applications, however, such additional information may be exploited most productively, since typical scenarios require the prediction of a wide range of individual characteristics from a range of available samples, biometric and non-biometric. In many such situations, it may be very useful to predict characteristics short of actual identity, since this type of prediction can significantly increase the amount of evidence available. In this paper we provide some benchmarking data to demonstrate the extent to which typical non-biometric information might be effective in practice in this context, and illustrate the differential effects depending on the classifier adopted. In particular, however, we investigate experimentally how traditionally measured handwritten signature data might be used to predict non-biometric categories in a way which can be exploited a variety of practical application scenarios.
Fingerprint Recognition System Based on Mapping Approach
"... Fingerprint identification system is mainly consisted of fingerprint achieving, fingerprint classification and fingerprint matching. Fingerprint matching is the key to the system and effects on the precision and efficiency of the whole system directly. Fingerprints are matched mainly based on their ..."
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Fingerprint identification system is mainly consisted of fingerprint achieving, fingerprint classification and fingerprint matching. Fingerprint matching is the key to the system and effects on the precision and efficiency of the whole system directly. Fingerprints are matched mainly based on their fingerprint texture pattern which can be described with the orientation field of fingerprints. A fingerprint, which has the different orientation angle structure in different local area of the fingerprint and has a texture pattern correlation among the neighboring local areas of the fingerprint, can be viewed as a Markov stochastic field. A novel method of fingerprint matching, which is based on embedded Hidden Markov Model (HMM) that is used for modeling the fingerprint’s orientation field, is described in this paper. The accurate and robust fingerprint matching can be achieved by matching embedded Hidden Markov Model parameters which were built after the processing of extracting features from a fingerprint, forming the samples of observation vectors and training the embedded Hidden Markov Model parameters.
Converting Fingerprint Local Features to Public Key Using Fuzzy Extractor
"... Biometric security systems are being widely used for ensuring maximum level of safety. In Biometric system, neither the data is uniformly distributed, nor can it be reproduced precisely. Each time it is processed. However, this processed data cannot be used as a password or as a cryptography secret. ..."
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Biometric security systems are being widely used for ensuring maximum level of safety. In Biometric system, neither the data is uniformly distributed, nor can it be reproduced precisely. Each time it is processed. However, this processed data cannot be used as a password or as a cryptography secret. This paper proposes a novel method to extract fingerprint minutiae features and converting it to a public key using the fuzzy extractor. The public key can be used as a key in a cryptographic application
Efficient Fingerprint Recognition System using Pseudo 2D Hidden Markov Model
"... Abstract- Fingerprint can only uniquely identify a person when compared to other types of biometric features. The existing system used the combination of bayes classifier and Henry classifier to increase the speed of authentication process and to provide accurate classification system respectively. ..."
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Abstract- Fingerprint can only uniquely identify a person when compared to other types of biometric features. The existing system used the combination of bayes classifier and Henry classifier to increase the speed of authentication process and to provide accurate classification system respectively. But, the combination of those classifiers in real time systems becomes difficult to implement. This fingerprint recognition system uses the pseudo 2D hidden markov model which considers each types of fingerprint as separate states with different levels of markov chain. During the recognition process, the markov model verifies each super states to identify which types of fingerprint, then it can match the given fingerprint image with the image which are kept in database. The proposed work will improve the speed and recognition rate by using the pseudo 2D hidden markov model. In global pattern matching, the global pattern [4] of Fingerprint consists of six patterns: arch, tented arch, right loop, left loop, whorl, and twin loop. But the enhanced fingerprint recognition process consider the four major categories like arch, right loop, left loop and whorl (as shown in Fig.2.) as the super states of pseudo 2D hidden markov chain[5]. The tended arch and twin loop categories of fingerprint are considered as sub states of arch and whorl super sates respectively. Each pattern can be compared by the flow of ridges between two fingerprint images. Keyword- fingerprint recognition, hidden markov model, viterbi algorithm, fingerprint classification. I.
ACKNOWLEDGMENTS
, 2005
"... This work is copyright. It may be reproduced in whole or in part for study or training purposes subject to the inclusion of an acknowledgment of the source and no commercial usage or sale. Reproduction for purposes other than those indicated above, requires the prior written permission from the Comm ..."
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This work is copyright. It may be reproduced in whole or in part for study or training purposes subject to the inclusion of an acknowledgment of the source and no commercial usage or sale. Reproduction for purposes other than those indicated above, requires the prior written permission from the Commonwealth. Requests and inquiries concerning reproduction and rights should be addressed to Commonwealth Copyright
Web site: www.itgi.org and www.isaca.org
"... The IT Governance Institute (ITGI) strives to assist enterprise leaders in their responsibility to make IT successful in supporting the enterprise’s mission and goals. Its goals are to raise awareness and understanding among and provide guidance and tools to boards of directors, executive management ..."
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The IT Governance Institute (ITGI) strives to assist enterprise leaders in their responsibility to make IT successful in supporting the enterprise’s mission and goals. Its goals are to raise awareness and understanding among and provide guidance and tools to boards of directors, executive management and chief information officers (CIOs) such that they are able to ensure within their enterprises that IT meets and exceeds expectations, and its risks are mitigated. Information Systems Audit and Control Association ® The Information Systems Audit and Control Association (ISACA ® ) is an international professional, technical and educational organization dedicated to being a recognized global leader in IT governance, security, control and assurance. With members in more than 100 countries, ISACA is uniquely positioned to fulfill the role of a central, harmonizing source of IT control practice standards the world over. Its strategic alliances with other organizations in the financial, accounting, auditing and IT professions ensure an unparalleled level of integration and commitment by business process owners. Disclaimer The IT Governance Institute, Information Systems Audit and Control Association and the author of Risk and Control of Biometric Technologies have designed the publication primarily as an educational resource for control professionals. ISACA makes no claim that use of this product will assure a successful outcome. The publication should not be considered inclusive of any proper procedures and tests or exclusive of other procedures and tests that are reasonably directed to obtaining the same
