Identix Corporation

Cognex Corporation

Morphotrust USA, LLC

Yasunari Tosa

David Usher

David Muller

Marc David Friedman

Nicholas A Accomando

Pablo Casaverde

Tim McNerney

Faisal Bashir

Vladimir Ruzhitsky

John Marshall

Don Yansen

David J Hitchcock

David J Michael

Juha Tapio Koljonen

Romina Marie Johnson Jose

Greg Heacock

Stephen F Daly

Ivan A Bachelder

Paul Dutta-Choudhury

Raymond A Fix

Venkat K Gopalakrishnan

Len L Picard

Karen Roberts

Nichoas A Accomando

Yun Chang

Rob Milligan

Gregory L Heacock

Therese Hunt

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.

Iris data extraction

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.

Multimodal ocular biometric system

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.

Multimodal ocular biometric system and methods

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.

Long distance multimodal biometric system and method

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.

A method and system create a geometric object model for use in machine vision inspection. A pixel image representation of an object is acquired. Based on this pixel image representation, part models for the parts of the object are generated. Each part model corresponds to a different part of the object. From the part models of the object, a model for the entire object can be created. Using this created object model, a test inspection is performed on a set of test images, and each of the test images is associated with a set of known inspection measurements. The test inspection produces a set of testing inspection measurements. If the test inspection yields satisfactory performance, the object models created are stored.

Creating geometric model descriptions for use in machine vision inspection systems

Methods and apparatuses are disclosed for defining a locus of viable points on an elongated object, such as a locus of viable bond points on a lead of a lead frame. The locus guides the bond point positioning of a wire bonder so that the number of unacceptable wire bonds is reduced. The locus is a region adapted to receive a bond, and is defined such that for any bond centered therein, the probability of forming an unacceptable bond is reduced by offsetting the locus from at least a portion of the lead edge(s) by a minimum-offset distance. The minimum-offset distance is based on various factor(s), such as user tolerance and bond width. Further, the definition of the locus is independent of lead shape, and consequently works with a variety of lead shapes. The locus can also have various shapes for a single lead, and the shapes can vary depending on the application. The method and apparatus herein disclosed describe a variety of methods to detect the leads and define the size, position, and shape of the locus during training. Preferably, the lead tip is also detected so that the locus can be defined based on an offset from the front of the lead. During operation, characteristics of the locus and/or the target bond point are used to relocate the lead and refine the target bond/point before bonding. Alternative embodiments disclosed include inspecting the leads.

Methods and apparatuses for defining a region on an elongated object

A machine vision system for identifying the locations of bonding pads on an integrated circuit mounted in a lead frame. The system involves locating the bonding pads by searching an image with suitably rotated corner templates. A set of possible candidate bonding pads is created from the location of corner templates found during the search. The set is then scored utilizing matching criteria. The best candidate is selected from the set based upon the candidates' scores. The location of the bonding pad is then generated from the best candidate's corner template locations. The invention can be beneficially applied to locate bonding pads during wire bonding, as well as other machine vision applications.

Template rotating method for locating bond pads in an image

A machine vision system for identifying the locations of bonding pads on an integrated circuit mounted in a lead frame. The system involves rotating the image of the die to produce an image of the die unrotated with respect to the lead frame (the 'counter-rotated image'). The counter-rotated image is searched with corner templates of the bonding pad. A set of possible candidate bonding pads is created from the location of corner templates found during the search. The set is then scored utilizing matching criteria. The best candidate is selected from the set based upon the candidates' scores. The location of the bonding pad is then generated from the best candidate's corner template locations. The invention can be beneficially applied to locate bonding pads during wire bonding, as well as other machine vision applications.

Image rotating method for locating bond pads in an image

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Arlington, MA, United States of America

Yasunari Tosa