Patent Publication Number: US-2013250087-A1

Title: Pre-processor imaging system and method for remotely capturing iris images

Description:
BACKGROUND 
     Iris recognition is important in multi-modal biometrics programs, but its use is limited by constraints on technology for capturing iris images. Currently, iris-based biometrics is confined to conditions that optimize obtaining high-resolution, high-contrast images. These conditions include careful positioning of a cooperative person willing to keep their head still and look into a limited field of view capture camera with suitable illumination. Typical systems require the person to be within 50 cm from the sensor and to remain stationary for up to ten seconds in-line with the scanning window. As a consequence, iris recognition systems have a reputation for being borderline intrusive, and less friendly for both subjects and operators. For some applications, such as security checkpoints, bank teller machines, or information technology (IT) access points, these limitations are acceptable. However, these constraints limit practical use for many applications, such as screening in airports, subway systems or at entrances to uncontrolled facilities where persons are moving and not visually fixated at one point. What is needed is a system that captures iris images while the person is in motion and at a substantial distance from a sensor. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       The detailed description will refer to the following drawings, wherein like numerals refer to like elements, and wherein: 
         FIG. 1  illustrates an embodiment of a pre-processor imaging system for remotely capturing iris images; 
         FIG. 2  illustrates an overall system architecture of an embodiment of a pre-processor imaging system; 
         FIG. 3  illustrates exemplary screenshots generated by an application program interface (API) showing face detection, eye position and head pose tracking; 
         FIG. 4  is a flow chart illustrating embodiment of a method for using the pre-processor imaging system of  FIG. 2  to remotely capture iris images; and 
         FIG. 5  is a block diagram illustrating exemplary hardware components for implementing embodiments of the pre-processor imaging system of  FIG. 2  and method of  FIG. 4  for remotely capturing iris images. 
     
    
    
     DETAILED DESCRIPTION 
     A pre-processor imaging system and method are disclosed for remotely capturing iris images of a target individual (i.e., subject or capture subject). In an embodiment, the pre-processor imaging system and method integrate an iris imaging system and a pre-processor that uses predictive head and eye tracking algorithms to predict a maximal opportunity window (i.e., optimal opportunity window) for capturing iris images. An embodiment of the pre-processor directs the iris imaging system to capture the iris images within the maximal opportunity window. In an embodiment, the iris imaging system includes a zoom camera and an infrared illumination system for reliably obtaining high-resolution iris images of each eye/iris region of the target individual, while the target individual is “on-the-move.” 
     An embodiment of the infrared illumination system uses a high-intensity infrared light source to illuminate eyes of the target individual to obtain high-speed images and reduce motion blur. An embodiment of the pre-processor imaging system and method uses bandwidth filters to eliminate noise from ambient light. An embodiment of the pre-processor may use a three-dimensional (3-D) head-eye position model to provide 3-D head and eye tracking. The integrated pre-processor imaging system, also referred to as an iris-capture breadboard, may serve as a platform for capturing iris images in moving subjects not fixating on the camera. 
       FIG. 1  illustrates an embodiment of a pre-processor imaging system for remotely capturing iris images. The pre-processor imaging system may provide 3-D head and eye tracking  120  of a target individual  110  to predict a maximal opportunity window  130  (i.e., optimal downstream iris-capture opportunity). The pre-processor imaging system may include one or more cameras primed to capture iris images  140 . The pre-processor imaging system optimizes the iris-capture opportunity, improves failure-to-acquire rates, and provides less intrusive and less constrained iris image acquisition by capturing iris images while the subjects are moving or uncooperative. 
       FIG. 2  illustrates an overall system architecture of an embodiment of a pre-processor imaging system  200 . The pre-processor imaging system  200  may use a field camera  202 , such as an inexpensive webcam, to observe the target individual  110  (i.e., subject or capture subject). The output of the field camera  202  may be fed to a software package  206  that determines a current eye location  208  and head-pose data  210 . The current eye location  208  may be the position of the eyes in a  3 -D space. The head-pose data  210  may be the position and rotation of the head in space relative to the field camera  202 . 
     The software package  206  may be an application program interface (API), such as faceAPI™, that implements a face detection algorithm, eye position detector, and a head pose estimator to determine the current eye location  208  and the head-pose data  210 .  FIG. 3  illustrates exemplary screenshots  300  generated by the API, such as faceAPI™, showing face detection, eye position and head pose tracking. 
     In the absence of a predictive algorithm, the current eye location  208  may be used to position a second, a zoom camera  204  (i.e., eye camera) to capture the iris images. The zoom camera  204  may be part of an iris imaging system (not shown) and may be a high quality zoom camera. The current eye location  208  may also be used to provide baseline information regarding acquisition rates. The baseline information may be iris-capture acquisition rates that the system captures an iris image considering lags in the positioning system, including video frame lags, eye position and head pose detection, and camera re-positioning. 
     The head-pose data  210  and the current eye location  208  may be used as inputs to a pre-processor  212  that uses a head movement model (e.g., predictive head and eye tracking algorithms) to predict a future eye location  214 , e.g., the location of the iris at a future point in time and space, and identify the maximal opportunity window  130  for iris-capture. In other words, the head-pose data  210  and the current eye location  208  are used by the pre-processor  212  to drive the zoom camera  204  to improve iris acquisition rates. 
     The head-pose data  210  and the current eye location  208  may provide historical data on the head movement pattern (i.e., head movement pattern data). The pre-processor  212  may use video imagery from the field camera  202  and head and eye movement behavioral characteristics to identify the maximal opportunity window  130  for iris-capture. The head and eye movement behavioral characteristics may be obtained by analyzing facial features and the head movement pattern data using, for example, the predictive head and eye tracking algorithms. 
     Examples of the predictive head and eye tracking algorithms include algorithms described in Three-Dimensional Model of the Human Eye-Head Saccadic System, by Douglas Tweed, The Journal of Neurophysiology Vol. 77 No. 2 February 1997, pp. 654-666, which is incorporated herein by reference. Alternate algorithms, based on similar approaches, or more simple control laws may also be used. The predictive head and eye tracking algorithms may predict the future eye location  214  and the next maximal opportunity window  130  for iris-capture. The maximal opportunity window  130  may be used to direct the zoom camera  204  to obtain close-up, high-resolution images of a rectangular region  132  (shown in  FIG. 1 ) that contains both eyes of the target individual  110 . 
     The predictive head and eye tracking algorithms may be provided in Matlab form and ported to Mathcad to test in an embodiment. In an embodiment, the Mathcad may be converted to C++. The pre-processor  212  may provide an integration tool that allows the output data, which is expressed as 3-D rotations of the head and eye in quaternion form, to be readily visualized. Quaternion form is a set of numbers that include a four-dimensional vector space with a basis including the real number 1 and three imaginary units i. j, k, that follow special rules of multiplication and that are used in computer graphics, robotics, and animation to rotate objects in three dimensions. The predictive head and eye tracking algorithms may predict the head and eye movements when a target individual moves from looking at a known fixed position (the starting position) to another known position (the target position). Both these positions may be provided as input data to explore the dynamics of head and eye movements, e.g., head movement pattern data. The head movement pattern data may be used as an input to predict the likely next movement in terms of magnitude and direction. 
     With reference to  FIG. 2  again, the pre-processor  212  may provide a scalable system that develops, tests, and tunes the predictive head and eye tracking algorithms to enhance iris-capture. For example, the predictive head and eye tracking algorithms may use the head movement pattern data to predict the future eye location  214  to position customized optical systems, such as the iris imaging system that includes the zoom camera  204 , to capture the iris images. 
     The pre-processor  212  may use non-contact, optical methods to measure eye motion based on, for example, light reflected from the eyes and sensed by the field camera  202 . The reflected light may be analyzed by the pre-processor  212  to extract eye rotation information based on changes in reflections. Also, a gaze direction may be predicted based on the visual environment. For example, people look at regular patterns more frequently than random patterns. Likewise, at airport security checkpoints, prior to the personal screener, passengers often look up to see if the green light is on. The pre-processor  212  may conduct an analysis of the visual environment to determine the likely salient features to guide system placement to optimize the observation point and may purposefully install salient features in the environment to attract attention. 
     Having identified the maximum opportunity window  130  that includes the future eye location  214 , the zoom camera  204  may be directed to take a sequence of close-up, high-resolution images of each eye/iris region to be used by iris recognition algorithms. High-intensity infrared light sources (not shown) may be used to provide sufficient illumination to obtain high-speed images with the zoom camera  204 . Bandwidth filters (not shown) may be used to eliminate noise from ambient light. 
     The zoom camera  204  may be, for example, a Sony Ipela pan, tilt and zoom (PTZ) network camera that aims at the eyes and captures the iris images, or a video camera directed through an X-Y steering mirror director system. The current eye location  208  may be extracted from data stream provided by the software package  206 , and fed to the zoom camera  204  through the pre-processor  212  on a frame by frame basis, for example, at 30 frames per second. The communication between the pre-processor and the zoom camera  204  may be through a direct drive protocol. 
     Embodiments of pre-processor imaging system  200  provide predictive head and eye movement models to enhance the capturing of iris images from target individuals in close open space, potentially without their knowledge. This technology has a wide variety of applications in a number of markets, including access control, identity services, and surveillance for airports, border control, government, military, and intelligence facilities. Face recognition systems may also benefit from the pre-processor imaging system, which may be used to anticipate when a face will be orthogonal to the camera, and thereby optimal for face capture. 
     Embodiments of pre-processor imaging system  200  may have applications outside the biometrics market. For instance, the human-machine interfacing challenges presented by video teleconferencing and in virtual worlds and gaming may benefit from this technology. The pre-processor imaging system  200  may be used to enhance the generation of synthetic images used to improve eye contact using stereo reconstruction techniques by anticipating head orientation for future frames, and may be used to enhance applications that seek to paint a webcam video of a participant&#39;s face onto an avatar in virtual worlds. In addition, by tracking and following the head movements of an individual, the pre-processor imaging system  200  may isolate suspicious behaviors or activities on the basis that the movement does not align with the major models of movement developed for this individual. 
       FIG. 4  is a flow chart illustrating embodiment of a method  400  for using the pre-processor imaging system  200  to remotely capture iris images. The method  400  starts (block  402 ) by directing at least one field camera to observe a target individual (block  404 ). Next, the method  400  determines a current eye location and head-pose data based on an output from the field camera (block  406 ). Then method  400  then identifies, using a pre-processor and predictive head and eye tracking algorithms, a maximal opportunity window for iris-capture (block  408 ). Finally, the method  400  directs at least one zoom camera to capture one or more iris images of the target individual within the maximal opportunity window (block  410 ) and ends at block  412 . 
       FIG. 5  is a block diagram illustrating exemplary hardware components for implementing embodiments of the pre-processor imaging system  200  and method  500  for remotely capturing iris images. A server  500 , or other computer system similarly configured, may include and execute programs to perform functions described herein, including steps of method  500  described above. Likewise, a mobile device that includes some of the same components of the computer system  500  may perform steps of the method  400  described above. The computer system  500  may connect with a network  518 , e.g., Internet, or other network, to receive inquires, obtain data, and transmit information and incentives as described above. 
     The computer system  500  typically includes a memory  502 , a secondary storage device  512 , and a processor  514 . The computer system  500  may also include a plurality of processors  514  and be configured as a plurality of, e.g., bladed servers, or other known server configurations. The computer system  500  may also include an input device  516 , a display device  510 , and an output device  508 . The memory  502  may include RAM or similar types of memory, and it may store one or more applications for execution by the processor  514 . The secondary storage device  512  may include a hard disk drive, floppy disk drive, CD-ROM drive, or other types of non-volatile data storage. The processor  514  executes the application(s), such as the software package  206 , which are stored in the memory  502  or the secondary storage  512 , or received from the Internet or other network  518 . The processing by the processor  514  may be implemented in software, such as software modules, for execution by computers or other machines. These applications preferably include instructions executable to perform the functions and methods described above and illustrated in the Figures herein. The applications preferably provide GUIs through which users may view and interact with the application(s), such as the software package  206 . 
     Also, as noted, the processor  514  may execute one or more software applications in order to provide the functions described in this specification, specifically to execute and perform the steps and functions in the methods described above. Such methods and the processing may be implemented in software, such as software modules, for execution by computers or other machines. The GUIs may be formatted, for example, as web pages in Hyper-Text Markup Language (HTML), Extensible Markup Language (XML) or in any other suitable form for presentation on a display device depending upon applications used by users to interact with the pre-processor imaging system  200 . 
     The input device  516  may include any device for entering information into the computer system  500 , such as a touch-screen, keyboard, mouse, cursor-control device, microphone, digital camera, video recorder or camcorder. The input device  516  may be used to enter information into GUIs during performance of the methods described above. The display device  510  may include any type of device for presenting visual information such as, for example, a computer monitor or flat-screen display (or mobile device screen). The display device  510  may display the GUIs and/or output from the software package  206 , for example. The output device  508  may include any type of device for presenting a hard copy of information, such as a printer, and other types of output devices include speakers or any device for providing information in audio form. 
     Examples of the computer system  500  include dedicated server computers, such as bladed servers, personal computers, laptop computers, notebook computers, palm top computers, network computers, mobile devices, or any processor-controlled device capable of executing a web browser or other type of application for interacting with the system. 
     Although only one computer system  500  is shown in detail, the pre-processor imaging system  200  may use multiple computer systems or servers as necessary or desired to support the users and may also use back-up or redundant servers to prevent network downtime in the event of a failure of a particular server. In addition, although the computer system  500  is depicted with various components, one skilled in the art will appreciate that the server can contain additional or different components. In addition, although aspects of an implementation consistent with the above are described as being stored in memory, one skilled in the art will appreciate that these aspects can also be stored on or read from other types of computer program products or computer-readable media, such as secondary storage devices, including hard disks, floppy disks, or CD-ROM; or other forms of RAM or ROM. The computer-readable media may include instructions for controlling a computer system, such as the computer system  500 , to perform a particular method, such as methods described above. 
     The terms and descriptions used herein are set forth by way of illustration only and are not meant as limitations. Those skilled in the art will recognize that many variations are possible within the spirit and scope of the invention as defined in the following claims, and their equivalents, in which all terms are to be understood in their broadest possible sense unless otherwise indicated.