2013 IEEE International Conference on Technologies for Homeland Security (HST), 2013
ABSTRACT Directional pyramidal filter banks as feature extractors for ocular vascular biometrics ... more ABSTRACT Directional pyramidal filter banks as feature extractors for ocular vascular biometrics are proposed. Apart from the red, green, and blue (RGB) format, we analyze the significance of using HSV, YCbCr, and layer combinations (R+Cr)/2, (G+Cr)/2, (B+Cr)/2. For classification, Linear Discriminant Analysis (LDA) is used. We outline the advantages of a Contourlet transform implementation for eye vein biometrics, based on vascular patterns seen on the white of the eye. The performance of the proposed algorithm is evaluated using Receiver Operating Characteristic (ROC) curves. Area under the curve (AUC), equal error rate (EER), and decidability values are used as performance metrics. The dataset consists of more than 1600 still images and video frames acquired in two separate sessions from 40 subjects. All images were captured from a distance of 5 feet using a DSLR camera with an attached white LED light source. We evaluate and discuss the results of cross matching features extracted from still images and video recordings of conjunctival vasculature patterns. The best AUC value of 0.9999 with an EER of 0.064% resulted from using Cb layer in YCbCr color space. The best (lowest value) EER of 0.032% was obtained with an AUC value of 0.9998 using the green layer of the RGB images.
The iris and more recently vascular patterns
seen on the white of the eye have been considered fo... more The iris and more recently vascular patterns seen on the white of the eye have been considered for ocular biometrics. The non-contact nature, uniqueness, and permanence of ocular features makes them promising. Among new challenges are to develop commercial systems for less constrained environments and at extended distances. Such systems need to have minimal burden on the user and be robust for non-cooperative users. We present the design and development of standoff system for noncooperative ocular biometrics using system integration approach. Review of existing commercial and experimental long-range biometric systems is presented. The process of selection of sensors and illumination techniques is described. The development of user interfaces and algorithms for a working prototype is explained. The performance is evaluated with images of 28 subjects, acquired at distances up to 9 meters. The conflicting requirements for the design of this standoff biometric system, and the resulting performance limitations with impact on image quality are discussed.
The current challenges to developing commercial
Ocular Biometric systems are to create applicatio... more The current challenges to developing commercial Ocular Biometric systems are to create applications that tolerate unconstrained environments. Designs for sensors, user interfaces, and algorithms must perform well under variable illumination, poses, and camera distances, with low-quality images, and within other real-world conditions. Practical deployment requires interoperability of data and processing algorithms from multiple systems. Facilitating meaningful progress ultimately demands Biometric Databases that contain real-world data. Accelerated standardization offers practical means to organize the tremendous volume of emerging biometric information. Standards enable data exchanges that are grounded on comparable and compatible formats. This paper describes the development of a research-oriented Ocular Biometric Database that contains images acquired in conditions relevant to unconstrained environments. The data was collected with different sensors and imaging systems under diverse conditions representing real-world applications. Images and related data were stored in a database adhering to extended biometric standards requirements and biometric datainterchange formats. Assessment and applicability reviews were performed on existing national and international standards pertaining to ocular biometrics and were used during the development. The paper describes the design approach with a goal to achieve interoperability and standardization of data and results. It also addresses recent developments in biometric data acquisition, pre- and post-processing, information storage, exchange, and access control.
Abstract— Directional pyramidal filter banks as feature extractors for ocular vascular biometrics... more Abstract— Directional pyramidal filter banks as feature extractors for ocular vascular biometrics are proposed. Apart from the red, green, and blue (RGB) format, we analyze the significance of using HSV, YCbCr, and layer combinations (R+Cr)/2, (G+Cr)/2, (B+Cr)/2. For classification, Linear Discriminant Analysis (LDA) is used. We outline the advantages of a Contourlet transform implementation for eye vein biometrics, based on vascular patterns seen on the white of the eye. The performance of the proposed algorithm is evaluated using Receiver Operating Characteristic (ROC) curves. Area under the curve (AUC), equal error rate (EER), and decidability values are used as performance metrics. The dataset consists of more than 1600 still images and video frames acquired in two separate sessions from 40 subjects. All images were captured from a distance of 5 feet using a DSLR camera with an attached white LED light source. We evaluate and discuss the results of cross matching features extracted from still images and video recordings of conjunctival vasculature patterns. The best AUC value of 0.9999 with an EER of 0.064% resulted from using Cb layer in YCbCr color space. The best (lowest value) EER of 0.032% was obtained with an
Besides the iris, conjunctival vasculature may also be used for ocular biometric recognition. Con... more Besides the iris, conjunctival vasculature may also be used for ocular biometric recognition. Conjunctival vessel patterns can be easily observed in the visible spectrum and can compensate for off-angle or otherwise occluded iridial texture. In this paper, classification of conjunctival vasculature using Gray Level Co-occurrence Matrix (GLCM) is studied. Statistical features of GLCM, i.e., contrast, correlation, energy and homogeneity, were used in conjunction with Fisher linear discriminant analysis and regularized neural network classifiers in order to recognize textures arising from conjunctival vessels. Match score level fusion of Fisher LDA and neural networks provided the best results, resulting in a test set equal error rate (EER) and area under receiver operating characteristics curve (ROC AUC) of 13.97% and 0.9333, respectively. These figures improved to 11.9% and 0.9504 after fusion of LDA and neural network match scores.
Electroencephalography (EEG) is a well developed technique used in many clinical and research app... more Electroencephalography (EEG) is a well developed technique used in many clinical and research applications. Continuous improvements on quality of scalp electrodes and front-end amplifiers, and data processing and storage have elevated EEG to a standard non-invasive method for monitoring many brain functions. EEG can also provide a new means for sending messages to the external world which is commonly known as a Brain-Computer Interface (BCI). This paper describes different feature extraction techniques for classification of recorded EEG signals. Time and frequency processing of multichannel EEG recordings during four a priori known mental tasks is presented. The four tasks include imagining the movement of an arm or a leg without the execution of the actual motion. During the recording sessions, the imagined movements are separated with intervals of subject relaxation. Different methods were used for feature extraction and classification of the EEG signals as a base for BCI. The results demonstrate that signals from an untrained subject can be classified successfully. The algorithms can be used to establish a real-time direct connection between mental task activity and external communication. In this regard we view the possibility for extending the neuroplasticity of the brain toward direct control of specifically designed external devices.
For more than a decade, Midwest Research Institute (MRI) has investigated the effects of exposure... more For more than a decade, Midwest Research Institute (MRI) has investigated the effects of exposure to 60 Hz electric and magnetic fields (EMF) on human physiology, performance, and biochemistry. This accumulated experience, new research directions, and limited resources made it important to design more comprehensive and operationally cost-effective exposure facilities. Here we describe the new, integrated laboratory exposure test facilities recently constructed at MRI and present data on relevant characteristics of the exposure systems. Concentric coil systems were developed to generate uniform magnetic fields within the three new exposure rooms, with rapid cancellation of the field to ambient levels in the rest of the laboratory. Control systems are fully automated, computer-based, and independent. These provide the operational flexibility needed to present fields of different magnitudes, frequencies, and polarization. The local geomagnetic field can be modulated and/or canceled, and both AC and DC fields can be presented in various combinations. Capabilities for conducting doubleblind experiments with true active-sham exposure conditions were implemented using bifilar windings and applying current flow in the opposite direction for each wire in a pair. The new facilities provide a comprehensive capability for laboratory-based human research on the potential effects of exposure to AC and DC magnetic fields. good environment for exposure testing with human † Current address for P. Doynov: 810 W. 54 th St., Kansas City, MO volunteers. The parameters of the exposure system 64112. performance of the exposure facility and on the stabilmriresearch.org ity of the exposure environment over time [Kaune
An analog device for automated real-time detection and short-term prediction of epileptic seizure... more An analog device for automated real-time detection and short-term prediction of epileptic seizures is described. In its basic form, the device utilizes a non-sorting analog percentile filtering to implement in analog form the FHS numerical seizure detection algorithm. The extensions and enhancements of the basic version of the device include (1) adjustment (individual adaptation) of the front-end filter for pre-processing the ECoG signal, or combining several filters in a `filter bank' to increase the reliability of detection, (2) adjustment of the parameters of the analog percentile filter to emphasize desirable signal features, and (3) utilization of a multi-channel percentile filter module with adjustable parameters. The described device can easily satisfy size, weight, and power criteria applicable to portable and/or implantable devices and combines the robustness and reliability of a generic algorithm with an easy adjustment (adaptation) to individual patients. Development of such a device will translate into better care for persons with epilepsy in a cost effective manner by minimising risk of injury or sudden death and improving quality of life by freeing them to pursue normal activities, including work
2013 IEEE International Conference on Technologies for Homeland Security (HST), 2013
ABSTRACT Directional pyramidal filter banks as feature extractors for ocular vascular biometrics ... more ABSTRACT Directional pyramidal filter banks as feature extractors for ocular vascular biometrics are proposed. Apart from the red, green, and blue (RGB) format, we analyze the significance of using HSV, YCbCr, and layer combinations (R+Cr)/2, (G+Cr)/2, (B+Cr)/2. For classification, Linear Discriminant Analysis (LDA) is used. We outline the advantages of a Contourlet transform implementation for eye vein biometrics, based on vascular patterns seen on the white of the eye. The performance of the proposed algorithm is evaluated using Receiver Operating Characteristic (ROC) curves. Area under the curve (AUC), equal error rate (EER), and decidability values are used as performance metrics. The dataset consists of more than 1600 still images and video frames acquired in two separate sessions from 40 subjects. All images were captured from a distance of 5 feet using a DSLR camera with an attached white LED light source. We evaluate and discuss the results of cross matching features extracted from still images and video recordings of conjunctival vasculature patterns. The best AUC value of 0.9999 with an EER of 0.064% resulted from using Cb layer in YCbCr color space. The best (lowest value) EER of 0.032% was obtained with an AUC value of 0.9998 using the green layer of the RGB images.
The iris and more recently vascular patterns
seen on the white of the eye have been considered fo... more The iris and more recently vascular patterns seen on the white of the eye have been considered for ocular biometrics. The non-contact nature, uniqueness, and permanence of ocular features makes them promising. Among new challenges are to develop commercial systems for less constrained environments and at extended distances. Such systems need to have minimal burden on the user and be robust for non-cooperative users. We present the design and development of standoff system for noncooperative ocular biometrics using system integration approach. Review of existing commercial and experimental long-range biometric systems is presented. The process of selection of sensors and illumination techniques is described. The development of user interfaces and algorithms for a working prototype is explained. The performance is evaluated with images of 28 subjects, acquired at distances up to 9 meters. The conflicting requirements for the design of this standoff biometric system, and the resulting performance limitations with impact on image quality are discussed.
The current challenges to developing commercial
Ocular Biometric systems are to create applicatio... more The current challenges to developing commercial Ocular Biometric systems are to create applications that tolerate unconstrained environments. Designs for sensors, user interfaces, and algorithms must perform well under variable illumination, poses, and camera distances, with low-quality images, and within other real-world conditions. Practical deployment requires interoperability of data and processing algorithms from multiple systems. Facilitating meaningful progress ultimately demands Biometric Databases that contain real-world data. Accelerated standardization offers practical means to organize the tremendous volume of emerging biometric information. Standards enable data exchanges that are grounded on comparable and compatible formats. This paper describes the development of a research-oriented Ocular Biometric Database that contains images acquired in conditions relevant to unconstrained environments. The data was collected with different sensors and imaging systems under diverse conditions representing real-world applications. Images and related data were stored in a database adhering to extended biometric standards requirements and biometric datainterchange formats. Assessment and applicability reviews were performed on existing national and international standards pertaining to ocular biometrics and were used during the development. The paper describes the design approach with a goal to achieve interoperability and standardization of data and results. It also addresses recent developments in biometric data acquisition, pre- and post-processing, information storage, exchange, and access control.
Abstract— Directional pyramidal filter banks as feature extractors for ocular vascular biometrics... more Abstract— Directional pyramidal filter banks as feature extractors for ocular vascular biometrics are proposed. Apart from the red, green, and blue (RGB) format, we analyze the significance of using HSV, YCbCr, and layer combinations (R+Cr)/2, (G+Cr)/2, (B+Cr)/2. For classification, Linear Discriminant Analysis (LDA) is used. We outline the advantages of a Contourlet transform implementation for eye vein biometrics, based on vascular patterns seen on the white of the eye. The performance of the proposed algorithm is evaluated using Receiver Operating Characteristic (ROC) curves. Area under the curve (AUC), equal error rate (EER), and decidability values are used as performance metrics. The dataset consists of more than 1600 still images and video frames acquired in two separate sessions from 40 subjects. All images were captured from a distance of 5 feet using a DSLR camera with an attached white LED light source. We evaluate and discuss the results of cross matching features extracted from still images and video recordings of conjunctival vasculature patterns. The best AUC value of 0.9999 with an EER of 0.064% resulted from using Cb layer in YCbCr color space. The best (lowest value) EER of 0.032% was obtained with an
Besides the iris, conjunctival vasculature may also be used for ocular biometric recognition. Con... more Besides the iris, conjunctival vasculature may also be used for ocular biometric recognition. Conjunctival vessel patterns can be easily observed in the visible spectrum and can compensate for off-angle or otherwise occluded iridial texture. In this paper, classification of conjunctival vasculature using Gray Level Co-occurrence Matrix (GLCM) is studied. Statistical features of GLCM, i.e., contrast, correlation, energy and homogeneity, were used in conjunction with Fisher linear discriminant analysis and regularized neural network classifiers in order to recognize textures arising from conjunctival vessels. Match score level fusion of Fisher LDA and neural networks provided the best results, resulting in a test set equal error rate (EER) and area under receiver operating characteristics curve (ROC AUC) of 13.97% and 0.9333, respectively. These figures improved to 11.9% and 0.9504 after fusion of LDA and neural network match scores.
Electroencephalography (EEG) is a well developed technique used in many clinical and research app... more Electroencephalography (EEG) is a well developed technique used in many clinical and research applications. Continuous improvements on quality of scalp electrodes and front-end amplifiers, and data processing and storage have elevated EEG to a standard non-invasive method for monitoring many brain functions. EEG can also provide a new means for sending messages to the external world which is commonly known as a Brain-Computer Interface (BCI). This paper describes different feature extraction techniques for classification of recorded EEG signals. Time and frequency processing of multichannel EEG recordings during four a priori known mental tasks is presented. The four tasks include imagining the movement of an arm or a leg without the execution of the actual motion. During the recording sessions, the imagined movements are separated with intervals of subject relaxation. Different methods were used for feature extraction and classification of the EEG signals as a base for BCI. The results demonstrate that signals from an untrained subject can be classified successfully. The algorithms can be used to establish a real-time direct connection between mental task activity and external communication. In this regard we view the possibility for extending the neuroplasticity of the brain toward direct control of specifically designed external devices.
For more than a decade, Midwest Research Institute (MRI) has investigated the effects of exposure... more For more than a decade, Midwest Research Institute (MRI) has investigated the effects of exposure to 60 Hz electric and magnetic fields (EMF) on human physiology, performance, and biochemistry. This accumulated experience, new research directions, and limited resources made it important to design more comprehensive and operationally cost-effective exposure facilities. Here we describe the new, integrated laboratory exposure test facilities recently constructed at MRI and present data on relevant characteristics of the exposure systems. Concentric coil systems were developed to generate uniform magnetic fields within the three new exposure rooms, with rapid cancellation of the field to ambient levels in the rest of the laboratory. Control systems are fully automated, computer-based, and independent. These provide the operational flexibility needed to present fields of different magnitudes, frequencies, and polarization. The local geomagnetic field can be modulated and/or canceled, and both AC and DC fields can be presented in various combinations. Capabilities for conducting doubleblind experiments with true active-sham exposure conditions were implemented using bifilar windings and applying current flow in the opposite direction for each wire in a pair. The new facilities provide a comprehensive capability for laboratory-based human research on the potential effects of exposure to AC and DC magnetic fields. good environment for exposure testing with human † Current address for P. Doynov: 810 W. 54 th St., Kansas City, MO volunteers. The parameters of the exposure system 64112. performance of the exposure facility and on the stabilmriresearch.org ity of the exposure environment over time [Kaune
An analog device for automated real-time detection and short-term prediction of epileptic seizure... more An analog device for automated real-time detection and short-term prediction of epileptic seizures is described. In its basic form, the device utilizes a non-sorting analog percentile filtering to implement in analog form the FHS numerical seizure detection algorithm. The extensions and enhancements of the basic version of the device include (1) adjustment (individual adaptation) of the front-end filter for pre-processing the ECoG signal, or combining several filters in a `filter bank' to increase the reliability of detection, (2) adjustment of the parameters of the analog percentile filter to emphasize desirable signal features, and (3) utilization of a multi-channel percentile filter module with adjustable parameters. The described device can easily satisfy size, weight, and power criteria applicable to portable and/or implantable devices and combines the robustness and reliability of a generic algorithm with an easy adjustment (adaptation) to individual patients. Development of such a device will translate into better care for persons with epilepsy in a cost effective manner by minimising risk of injury or sudden death and improving quality of life by freeing them to pursue normal activities, including work
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Papers by Plamen Doynov
seen on the white of the eye have been considered for
ocular biometrics. The non-contact nature, uniqueness,
and permanence of ocular features makes them promising.
Among new challenges are to develop commercial systems
for less constrained environments and at extended
distances. Such systems need to have minimal burden on
the user and be robust for non-cooperative users.
We present the design and development of standoff
system for noncooperative ocular biometrics using system
integration approach. Review of existing commercial and
experimental long-range biometric systems is presented.
The process of selection of sensors and illumination
techniques is described. The development of user
interfaces and algorithms for a working prototype is
explained. The performance is evaluated with images of 28
subjects, acquired at distances up to 9 meters. The
conflicting requirements for the design of this standoff
biometric system, and the resulting performance
limitations with impact on image quality are discussed.
Ocular Biometric systems are to create applications that tolerate
unconstrained environments. Designs for sensors, user interfaces,
and algorithms must perform well under variable illumination,
poses, and camera distances, with low-quality images, and within
other real-world conditions. Practical deployment requires
interoperability of data and processing algorithms from multiple
systems. Facilitating meaningful progress ultimately demands
Biometric Databases that contain real-world data. Accelerated
standardization offers practical means to organize the
tremendous volume of emerging biometric information.
Standards enable data exchanges that are grounded on
comparable and compatible formats.
This paper describes the development of a research-oriented
Ocular Biometric Database that contains images acquired in
conditions relevant to unconstrained environments. The data was
collected with different sensors and imaging systems under
diverse conditions representing real-world applications. Images
and related data were stored in a database adhering to extended
biometric standards requirements and biometric datainterchange
formats. Assessment and applicability reviews were
performed on existing national and international standards
pertaining to ocular biometrics and were used during the
development. The paper describes the design approach with a
goal to achieve interoperability and standardization of data and
results. It also addresses recent developments in biometric data
acquisition, pre- and post-processing, information storage,
exchange, and access control.
seen on the white of the eye have been considered for
ocular biometrics. The non-contact nature, uniqueness,
and permanence of ocular features makes them promising.
Among new challenges are to develop commercial systems
for less constrained environments and at extended
distances. Such systems need to have minimal burden on
the user and be robust for non-cooperative users.
We present the design and development of standoff
system for noncooperative ocular biometrics using system
integration approach. Review of existing commercial and
experimental long-range biometric systems is presented.
The process of selection of sensors and illumination
techniques is described. The development of user
interfaces and algorithms for a working prototype is
explained. The performance is evaluated with images of 28
subjects, acquired at distances up to 9 meters. The
conflicting requirements for the design of this standoff
biometric system, and the resulting performance
limitations with impact on image quality are discussed.
Ocular Biometric systems are to create applications that tolerate
unconstrained environments. Designs for sensors, user interfaces,
and algorithms must perform well under variable illumination,
poses, and camera distances, with low-quality images, and within
other real-world conditions. Practical deployment requires
interoperability of data and processing algorithms from multiple
systems. Facilitating meaningful progress ultimately demands
Biometric Databases that contain real-world data. Accelerated
standardization offers practical means to organize the
tremendous volume of emerging biometric information.
Standards enable data exchanges that are grounded on
comparable and compatible formats.
This paper describes the development of a research-oriented
Ocular Biometric Database that contains images acquired in
conditions relevant to unconstrained environments. The data was
collected with different sensors and imaging systems under
diverse conditions representing real-world applications. Images
and related data were stored in a database adhering to extended
biometric standards requirements and biometric datainterchange
formats. Assessment and applicability reviews were
performed on existing national and international standards
pertaining to ocular biometrics and were used during the
development. The paper describes the design approach with a
goal to achieve interoperability and standardization of data and
results. It also addresses recent developments in biometric data
acquisition, pre- and post-processing, information storage,
exchange, and access control.