Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: A multimodal biometric identification system captures and processes images of both the iris and the retina for biometric identification. Another multimodal ocular system captures and processes images of the iris and/or the from both eyes of a subject. Biometrics based on data provided by these systems are more accurate and robust than using biometrics that include data from only the iris or only the retina from a single eye. An exemplary embodiment emits photons to the iris and the retina of both eyes, an iris image sensor that captures an image of the iris when the iris reflects the emitted light, a retina image sensor that captures an image of the retina when the retina reflects the emitted light, and a controller that controls the iris and the retina illumination sources, where the captured image of the iris and the captured image of the retina contain biometric data.

Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: Biometric systems capture and combine biometric information from more than one modality, employing digital processing algorithms to process and evaluate captured images having data for a biometric characteristic. Such digital algorithms may include a pupil segmentation algorithm for determining a pupil image in the captured image, an iris segmentation algorithm for determining an iris image in the captured image, an eyelid/eyelash segmentation algorithm for determining an eyelid/eyelash image in the captured image, and an algorithm for measuring the focus on the iris. Some embodiments employ an auto-capture process which employs such algorithms, in part; to evaluate captured images and obtain the best possible images for biometric identification.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.

Abstract: A multimodal biometric identification system captures and processes images of both the iris and the retina for biometric identification. Another multimodal ocular system captures and processes images of the iris and/or the from both eyes of a subject. Biometrics based on data provided by these systems are more accurate and robust than using biometrics that include data from only the iris or only the retina from a single eye. An exemplary embodiment emits photons to the iris and the retina of both eyes, an iris image sensor that captures an image of the iris when the iris reflects the emitted light, a retina image sensor that captures an image of the retina when the retina reflects the emitted light, and a controller that controls the iris and the retina illumination sources, where the captured image of the iris and the captured image of the retina contain biometric data.

Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: Biometric systems capture and combine biometric information from more than one modality, employing digital processing algorithms to process and evaluate captured images having data for a biometric characteristic. Such digital algorithms may include a pupil segmentation algorithm for determining a pupil image in the captured image, an iris segmentation algorithm for determining an iris image in the captured image, an eyelid/eyelash segmentation algorithm for determining an eyelid/eyelash image in the captured image, and an algorithm for measuring the focus on the iris. Some embodiments employ an auto-capture process which employs such algorithms, in part; to evaluate captured images and obtain the best possible images for biometric identification.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.

Abstract: Biometric systems capture and combine biometric information from more than one modality, employing digital processing algorithms to process and evaluate captured images having data for a biometric characteristic. Such digital algorithms may include a pupil segmentation algorithm for determining a pupil image in the captured image, an iris segmentation algorithm for determining an iris image in the captured image, an eyelid/eyelash segmentation algorithm for determining an eyelid/eyelash image in the captured image, and an algorithm for measuring the focus on the iris. Some embodiments employ an auto-capture process which employs such algorithms, in part, to evaluate captured images and obtain the best possible images for biometric identification.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.

Abstract: A multimodal biometric identification system captures and processes images of both the iris and the retina for biometric identification. Another multimodal ocular system captures and processes images of the iris and/or the from both eyes of a subject. Biometrics based on data provided by these systems are more accurate and robust than using biometrics that include data from only the iris or only the retina from a single eye. An exemplary embodiment emits photons to the iris and the retina of both eyes, an iris image sensor that captures an image of the iris when the iris reflects the emitted light, a retina image sensor that captures an image of the retina when the retina reflects the emitted light, and a controller that controls the iris and the retina illumination sources, where the captured image of the iris and the captured image of the retina contain biometric data.

Abstract: A multimodal biometric identification system captures and processes images of both the iris and the retina for biometric identification. Another multimodal ocular system captures and processes images of the iris and/or the from both eyes of a subject. Biometrics based on data provided by these systems are more accurate and robust than using biometrics that include data from only the iris or only the retina from a single eye. An exemplary embodiment emits photons to the iris and the retina of both eyes, an iris image sensor that captures an image of the iris when the iris reflects the emitted light, a retina image sensor that captures an image of the retina when the retina reflects the emitted light, and a controller that controls the iris and the retina illumination sources, where the captured image of the iris and the captured image of the retina contain biometric data.

Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.

Abstract: A process for extracting iris data for biometric identification includes a thresholding method where the thresholds are selected according to a nonparametric approach that considers the grey scale and does not require classifying pixels as edge or non-edge pixels. An eye image is first acquired, where the eye image has component images including an iris image with an inner boundary and an outer boundary. The eye image has a distribution of grey levels. Component images, such as an iris image or a pupil image, from the eye image are segmented according to the distribution of grey levels. The inner boundary and outer boundary of the iris image are determined from the component images. The iris image within the inner boundary and outer boundary is processed for biometric identification. The component images may be segmented by creating an eye histogram of pixel intensities from the distribution of grey levels.

Abstract: Biometric systems capture and combine biometric information from more than one modality, employing digital processing algorithms to process and evaluate captured images having data for a biometric characteristic. Such digital algorithms may include a pupil segmentation algorithm for determining a pupil image in the captured image, an iris segmentation algorithm for determining an iris image in the captured image, an eyelid/eyelash segmentation algorithm for determining an eyelid/eyelash image in the captured image, and an algorithm for measuring the focus on the iris. Some embodiments employ an auto-capture process which employs such algorithms, in part, to evaluate captured images and obtain the best possible images for biometric identification.

Abstract: A system for multimodal biometric identification has a first imaging system that detects one or more subjects in a first field of view, including a targeted subject having a first biometric characteristic and a second biometric characteristic; a second imaging system that captures a first image of the first biometric characteristic according to first photons, where the first biometric characteristic is positioned in a second field of view smaller than the first field of view, and the first image includes first data for biometric identification; a third imaging system that captures a second image of the second biometric characteristic according to second photons, where the second biometric characteristic is positioned in a third field of view which is smaller than the first and second fields of view, and the second image includes second data for biometric identification. At least one active illumination source emits the second photons.