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Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

Technology: general issues --- online signature verification --- shape contexts --- function features --- SC-DTW --- symbolic representation --- two-stage method --- finger features --- multimodal recognition --- local coding --- Gabor filter --- LGS --- human identification --- biomarker --- ECG --- machine learning --- Physionet --- Lviv Biometric Dataset --- biometry --- identification --- bloodstream --- image recognition --- multi-biometrics --- bit planes --- block --- mutual information --- cross-device --- dorsal hand vein recognition --- person re-identification --- superpixel --- temporally aligned pooling --- walking cycle --- automatic recognition --- face --- voice --- body motion --- autism spectrum disorder (ASD) --- assessment --- intervention --- curve similarity --- curve similarity model --- curve similarity transformation --- similarity distance --- segmentation matching --- evolutionary computation --- finger vein recognition --- hand vein recognition --- contactless acquisition device --- public vascular pattern dataset --- biometric recognition performance evaluation --- face verification --- optical correlation --- Hausdorff distance --- image classification --- face detection --- depth map ensemble --- filtering --- geometric deep learning --- ear detection --- structured prediction --- semantic segmentation --- rotation equivariance --- Gaussian mixture model --- superpixels --- face recognition systems --- person identification --- biometric systems --- survey --- automatic signature verification --- touch-screen sensor --- data quality --- enrollment phase --- performance assessment --- augmented signature --- security enhancement --- mobile conditions --- biometric recognition --- visible light iris images --- image quality assessment --- image covariates --- quality filtering --- vascular biometric recognition --- wrist vein recognition --- contactless dataset --- pattern recognition --- infrared camera --- non-contact devices --- Scale-Invariant Feature Transform (SIFT®) --- Speeded Up Robust Features (SURF®) --- Oriented FAST and Rotated BRIEF (ORB) --- fingerprint --- presentation attack detection --- deep learning

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

Technology: general issues --- online signature verification --- shape contexts --- function features --- SC-DTW --- symbolic representation --- two-stage method --- finger features --- multimodal recognition --- local coding --- Gabor filter --- LGS --- human identification --- biomarker --- ECG --- machine learning --- Physionet --- Lviv Biometric Dataset --- biometry --- identification --- bloodstream --- image recognition --- multi-biometrics --- bit planes --- block --- mutual information --- cross-device --- dorsal hand vein recognition --- person re-identification --- superpixel --- temporally aligned pooling --- walking cycle --- automatic recognition --- face --- voice --- body motion --- autism spectrum disorder (ASD) --- assessment --- intervention --- curve similarity --- curve similarity model --- curve similarity transformation --- similarity distance --- segmentation matching --- evolutionary computation --- finger vein recognition --- hand vein recognition --- contactless acquisition device --- public vascular pattern dataset --- biometric recognition performance evaluation --- face verification --- optical correlation --- Hausdorff distance --- image classification --- face detection --- depth map ensemble --- filtering --- geometric deep learning --- ear detection --- structured prediction --- semantic segmentation --- rotation equivariance --- Gaussian mixture model --- superpixels --- face recognition systems --- person identification --- biometric systems --- survey --- automatic signature verification --- touch-screen sensor --- data quality --- enrollment phase --- performance assessment --- augmented signature --- security enhancement --- mobile conditions --- biometric recognition --- visible light iris images --- image quality assessment --- image covariates --- quality filtering --- vascular biometric recognition --- wrist vein recognition --- contactless dataset --- pattern recognition --- infrared camera --- non-contact devices --- Scale-Invariant Feature Transform (SIFT®) --- Speeded Up Robust Features (SURF®) --- Oriented FAST and Rotated BRIEF (ORB) --- fingerprint --- presentation attack detection --- deep learning