Full metadata record
DC FieldValueLanguage
dc.contributor.editorRatha, Nalini K.-
dc.contributor.editorGovindaraju, Venu-
dc.date.accessioned2017-04-04T07:56:44Z-
dc.date.available2017-04-04T07:56:44Z-
dc.date.issued2008-
dc.identifier.isbn978-1-84628-920-0-
dc.identifier.urihttp://repository.vnu.edu.vn/handle/VNU_123/24111-
dc.description.abstractRecognizing people based on their physiological or behavioral characteristics is the main focus of the science of biometrics. With the ever-increasing need for secure and reliable human identification methods in a highly security-conscious society spurred by recent events around the world, biometrics has surged from an interesting application of pattern-recognition techniques to a vibrant mainstream research topic over the last decade. The exponential growth of research in this area focuses on many challenging research prob-lems including evaluating new biometrics techniques, significantly improving accuracy in many existing biometrics, new sensing techniques, and large-scale system design issues. Biometrics technology relies on advances in many allied areas including pattern recognition, computer vision, signal/image processing, statistics, electrical engineering, computer science, and machine learning. Sev-eral books, conferences, and special issues of journals have been published and many are in the active pipeline covering these advanced research topics. Most of the published work assumes the biometric signal has been reliably acquired by the sensors and the task is one of controlling false match and false rejection rates. Thus, the focus and thrust of many researchers have been on pattern recognition and machine-learning algorithms in recognizing biometrics signals. However, the emphasis on the sensors themselves, which are critical in capturing high-quality signals, has been largely missing from the research discourse. We have endeavored to remedy this by including several chapters relating to the sensors for the various biometric modalities. This is perhaps the first book to provide a comprehensive treatment of the topic. Although covering the sensing aspect of biometrics at length, we are also equally excited about new algorithmic advances fundamentally changing the course for some of the leading and popular biometrics modalities as well as new modalities that may hold a new future. There has also been interest at the systems level both from a human factors point of view and the perspective of networking,vi databases, privacy, and antispoofing. Our goal in designing this book has been primarily based on covering many recent advances made in these three key areas: sensors, algorithms, and systems.-
dc.format.extent504 p.-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectComputer Scienceen_US
dc.titleAdvances in Biometricsen_US
dc.typeBooken_US
Appears in Collections:000 - Tin học, thông tin và tác phẩm tổng quát


  • 71.pdf
    • Size : 48,79 MB

    • Format : Adobe PDF

    • View : 
    • Download : 
  • Full metadata record
    DC FieldValueLanguage
    dc.contributor.editorRatha, Nalini K.-
    dc.contributor.editorGovindaraju, Venu-
    dc.date.accessioned2017-04-04T07:56:44Z-
    dc.date.available2017-04-04T07:56:44Z-
    dc.date.issued2008-
    dc.identifier.isbn978-1-84628-920-0-
    dc.identifier.urihttp://repository.vnu.edu.vn/handle/VNU_123/24111-
    dc.description.abstractRecognizing people based on their physiological or behavioral characteristics is the main focus of the science of biometrics. With the ever-increasing need for secure and reliable human identification methods in a highly security-conscious society spurred by recent events around the world, biometrics has surged from an interesting application of pattern-recognition techniques to a vibrant mainstream research topic over the last decade. The exponential growth of research in this area focuses on many challenging research prob-lems including evaluating new biometrics techniques, significantly improving accuracy in many existing biometrics, new sensing techniques, and large-scale system design issues. Biometrics technology relies on advances in many allied areas including pattern recognition, computer vision, signal/image processing, statistics, electrical engineering, computer science, and machine learning. Sev-eral books, conferences, and special issues of journals have been published and many are in the active pipeline covering these advanced research topics. Most of the published work assumes the biometric signal has been reliably acquired by the sensors and the task is one of controlling false match and false rejection rates. Thus, the focus and thrust of many researchers have been on pattern recognition and machine-learning algorithms in recognizing biometrics signals. However, the emphasis on the sensors themselves, which are critical in capturing high-quality signals, has been largely missing from the research discourse. We have endeavored to remedy this by including several chapters relating to the sensors for the various biometric modalities. This is perhaps the first book to provide a comprehensive treatment of the topic. Although covering the sensing aspect of biometrics at length, we are also equally excited about new algorithmic advances fundamentally changing the course for some of the leading and popular biometrics modalities as well as new modalities that may hold a new future. There has also been interest at the systems level both from a human factors point of view and the perspective of networking,vi databases, privacy, and antispoofing. Our goal in designing this book has been primarily based on covering many recent advances made in these three key areas: sensors, algorithms, and systems.-
    dc.format.extent504 p.-
    dc.language.isoenen_US
    dc.publisherSpringeren_US
    dc.subjectComputer Scienceen_US
    dc.titleAdvances in Biometricsen_US
    dc.typeBooken_US
    Appears in Collections:000 - Tin học, thông tin và tác phẩm tổng quát


  • 71.pdf
    • Size : 48,79 MB

    • Format : Adobe PDF

    • View : 
    • Download :