US20020154794A1 - Non-contact type human iris recognition method for correcting a rotated iris image - Google Patents

Non-contact type human iris recognition method for correcting a rotated iris image Download PDF

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Publication number
US20020154794A1
US20020154794A1 US10/017,118 US1711801A US2002154794A1 US 20020154794 A1 US20020154794 A1 US 20020154794A1 US 1711801 A US1711801 A US 1711801A US 2002154794 A1 US2002154794 A1 US 2002154794A1
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iris
image
iris image
polar coordinates
rotated
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US10/017,118
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Seong-Won Cho
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EVERMEDIA Co Ltd
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EVERMEDIA Co Ltd
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Publication of US20020154794A1 publication Critical patent/US20020154794A1/en
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/193—Preprocessing; Feature extraction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/143—Sensing or illuminating at different wavelengths
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/24—Aligning, centring, orientation detection or correction of the image
    • G06V10/242—Aligning, centring, orientation detection or correction of the image by image rotation, e.g. by 90 degrees
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
    • G06V10/478—Contour-based spectral representations or scale-space representations, e.g. by Fourier analysis, wavelet analysis or curvature scale-space [CSS]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/19—Sensors therefor

Definitions

  • the present invention relates to a non-contact iris recognition method of authenticating the identity of a person. More particularly, the present invention relates to a method for correcting a rotated iris image during the authentication process.
  • An iris recognition system is used for identifying the identity of a person by distinguishing one's own particular iris pattern.
  • the iris recognition system is superior in its accuracy in terms of personal identification compared to the other biometric methods, such as voice or fingerprint.
  • the iris identification system In order to solve the above problem associated with obtaining an accurate eye image, the iris identification system must accurately detect the inner/outer boundaries of the iris region and correct the iris image as needed.
  • most conventional iris recognition methods have drawbacks in that they cannot accurately detect the deformed or slanted eye image, other than manually readjusting the image after defining an arbitrary center of the pupil or using a mean value of the entire image to readjust the slanted image. Accordingly, there is a need for an iris recognition method to normalize the rotated or slanted iris image in response to when the subject eye is not directly facing the front of the camera, or the rotated iris image is caused by the movement of the user, i.e., tilting one's head.
  • the present invention provides a non-contact iris recognition method for authenticating the identification of a person.
  • One aspect of the present invention provides a human iris recognition method, such that in the event that the iris image is rotated by an angle, the rotated iris image is corrected into a normal iris image.
  • the iris image with an irregular shape is converted into polar coordinates so that the slanted iris image is reflected at a lower portion of the converted iris image in the polar coordinates.
  • the iris image is normalized to predetermined dimensions, so that the iris image with a variety of deformations is corrected.
  • Another aspect of the invention provides the method of detecting an iris image from the eye image of a user using an image acquisition device and converting the iris image in polar coordinates, wherein the inner and outer boundaries of an iris are detected using a Canny edge detector and infrared illuminator.
  • the method of converting to the polar coordinates further includes the steps of: comparing the pixel value of the image information at the center coordinates (x, y) of the detected inner boundary of the iris with the other pixel values of image information, which is obtained by measuring the upward, downward, leftward, and rightward directions from the inner boundary; determining the maximum value among the compared pixel values and detecting the outer boundary of the iris; extracting an iris region, defining the region between the inner and outer boundaries; and, converting the extracted iris region into the polar coordinates.
  • Another aspect of the inventive method provides, if the iris in the acquired eye image has been slanted, the step of normalizing the converted iris image in the polar coordinates so as to have predetermined dimensions.
  • Another aspect of the inventive method provides, if the iris in the acquired eye image has been rotated at an angle with respect to the centerline of the iris, the steps of temporarily generating a plurality of arrays of the iris image caused by the shifts with respect to an array of the converted iris image in the polar coordinates; performing the wavelet transform to generate the characteristic vectors of the iris corresponding to the plurality of arrays of the iris image that have been temporarily generated; comparing the respective characteristic vectors generated by the wavelet transform with the previously registered characteristic vectors to obtain similarities; and, accepting a characteristic vector corresponding to the maximum similarity among the obtained similarities as the characteristic vector of the user.
  • FIG. 1 is a flowchart explaining the operation steps of normalizing the iris image of a person according to the present invention.
  • FIG. 2 a is a view showing the detection result of a pupil boundary using a Canny edge detector.
  • FIG. 2 b is a view showing the center coordinates and the diameter of a pupil.
  • FIG. 2 c shows an iris image upon obtaining the radius and the center of the outer boundary of an iris according to the present invention.
  • FIGS. 3 ( a ) to ( d ) show the process of normalizing a slanted iris image.
  • FIGS. 4 ( a ) and ( b ) show a rotated iris image resulting from the tilting of a head.
  • FIGS. 5 ( a ) and ( b ) show the process of correcting the rotated iris image shown in FIGS. 4 ( a ) and ( b ).
  • FIG. 1 is a flowchart illustrating the operation steps of normalizing the iris image of a person according to the present invention.
  • the eye image is acquired using any commercially available image acquisition device equipped with an infrared illuminator and a visible light rejection filter.
  • the image acquisition device typically generates a reflective light to be gathered in the pupil of the eye region, so that information indicative of the iris image can be generated.
  • the inner and outer boundaries of the iris are detected to extract only the iris region from the acquired eye image, then the center of the detected inner and outer boundaries is set.
  • Step 120 can be performed in a variety of ways using a well-known method known to those skilled in this art.
  • detecting the inner and outer boundaries of the iris using the differences in pixels can be performed using a Canny edge detector. See for example, U.S. Pat. No. 5,566,246 filed on Jun. 7, 1996, the content of which is hereby incorporated by reference.
  • FIG. 2 a is an exemplary view illustrating the detection result of a pupillary boundary, i.e., the inner boundary of the iris, using the Canny edge detector.
  • a pupillary boundary i.e., the inner boundary of the iris
  • the Canny edge detector smoothes the acquired image using Gaussian filtering and then detects the boundary using a Sobel operation.
  • the Gaussian filtering process can be expressed as shown in Equation 1, and the Sobel operation can be expressed as Equation 2.
  • FIG. 2 b shows the center coordinates and diameter of the pupil detected. As shown in FIG. 2 b, the pupil's radius is d/2, and the pupil's center coordinates are (x+d/2, y+d/2).
  • the outer boundary of the iris can be detected by determining the pixel values away from the upward, downward, leftward, and rightward directions of the pupillary boundary, i.e., the inner boundary of the iris, where the maximum values of differences occur in the pixel values.
  • the detected maximum values are represented by Max ⁇ I(x, y) ⁇ I(x ⁇ 1, y) ⁇ , Max ⁇ I(x, y) ⁇ I(x+1, y) ⁇ , Max ⁇ I(x, y) ⁇ I(x, y ⁇ 1) ⁇ , and Max ⁇ I(x, y) ⁇ I(x, y+1) ⁇ , where I(x, y) represents the pixel value of the image at the point of (x, y).
  • the inner and outer centers should be adjusted accordingly.
  • FIG. 2 c shows the iris image after determining the radius and the center of the outer boundary of the iris according to the present invention. If an incomplete eye image is obtained as the eye is not directly facing the front of the camera and positioned at a slight angle with respect to the camera, the process of adjusting the centers of the inner/outer boundaries of the iris is required. First, the radial distances R L , R R , R u , and R D extending from the inner boundary to the left, right, upper, and lower portions to the outer boundary, respectively, and the radius RI of the inner boundary, i.e., the pupillary boundary, are calculated. The center of the outer boundary is obtained by determining the bisection points among the upward, downward, leftward, and rightward regions of the calculated values.
  • step 130 iris patterns are detected only at predetermined radial distances from the inner boundary to the outer boundary (explained later).
  • step 140 the detected iris pattern is converted into polar coordinates as shown in FIG. 3.
  • step 150 the converted iris image in the polar coordinates is normalized to obtain an image with predetermined dimensions in its width and height as discussed below.
  • Equation 3 The conversion of the extracted iris patterns into the iris image in the polar coordinates can be expressed as the following Equation 3:
  • ⁇ is increased by 0.8 degrees
  • r is calculated by using the second Cosine Rule from the distance between the outer center C O and the inner center C I of the iris, the radius R O of the outer boundary, and the value of ⁇ .
  • FIG. 3( a ) shows the slanted iris image.
  • FIG. 3( b ) shows the iris image in polar coordinates converted from the slanted iris image, as described in the preceding paragraph. It can be seen from FIG. 3( b ) that the lower portion of the converted iris image in the polar coordinates is curved with an irregular shape, which is caused by the slanted iris image.
  • FIG. 3( c ) shows an iris image with the dimensions of M pixels in width and N pixels in height which is normalized from the irregular image of the iris patterns shown in FIG. 3( b ).
  • the normalization process of the slanted iris image will be described with reference to FIGS. 3 ( a ) to ( c ).
  • the iris patterns existing at only a portion corresponding to a certain amount, X %, of the distance between the inner and outer boundaries of the iris are taken to eliminate interference from the illuminator. That is, when the inner and outer boundaries of the iris are detected, the iris patterns are taken and then converted into the polar coordinates.
  • iris patterns existing at only a portion corresponding to 60% of the distance from the inner boundary among the region from the inner boundary (pupillary boundary) of the iris to the outer boundary are converted into those in the polar coordinates.
  • the value of the 60% selected in this embodiment of the present invention was experimentally determined as a range in which the greatest deal of iris patterns can be picked up, while excluding the reflective light gathered on the iris.
  • the slanted iris image is converted into the iris image in the polar coordinates.
  • the lower portion of the converted iris pattern image in the polar coordinates is curved having an irregular shape due to a slanted iris image.
  • the irregular image of the iris patterns is normalized to obtain the iris image with the dimensions of M pixels in width and N pixels in height, by scaling up/down the iris image using the nearest neighbor pixel interpolation.
  • the performance of the iris recognition system is evaluated by two factors: a false acceptance rate (FAR) and a false rejection rate (FRR).
  • FAR indicates the probability that the iris recognition system incorrectly identifies an impostor as an enrollee and thus allows entrance of the impostor.
  • FRR indicates the probability that the iris recognition system incorrectly identifies the enrollee as an impostor and thus rejects entrance to the enrollee.
  • the inventive method of detecting the boundaries of the iris and normalizing the slanted iris image produce the FAR that was reduced from 5.5% to 2.83% and the FRR that was reduced from 5.0% to 2.0% as compared with the conventional iris recognition system.
  • step 160 if the iris in the detected eye image is rotated at an angle with respect to the centerline of the iris during the operation, the arrays of the pixels of the iris image information are moved. Hence, a correction of the rotated iris image is performed as described below.
  • FIGS. 4 ( a ) to ( b ) show the rotated iris image resulting from the tilting of the user's head.
  • the user's head may be tilted slightly toward the left or right, as shown in FIG. 4( a ).
  • FIG. 4( a ) shows the iris image rotated by about 15 degrees in a clockwise or counterclockwise direction depending on the direction of the head tilt with respect to the centerline of the eye.
  • the rotated iris image is converted into an image in the polar coordinates, the iris patterns in the converted image are shifted leftward or rightward as shown in FIG. 4( b ) based on the rotation direction of the angle.
  • FIGS. 5 ( a ) and ( b ) show the process of correcting the rotated iris images shown in FIGS. 4 ( a ) and ( b ).
  • the process of correcting the rotated iris image, which has resulted from the tilting of the user's head, through comparing and moving the arrays of the iris image information will be described below with reference to FIGS. 5 ( a ) and ( b ).
  • a plurality of arrays of the iris image are temporarily generated with respect to the Array( 0 ) of the converted iris image in the polar coordinates. That is, by shifting columns leftward or rightward of the Array( 0 ) based on the Array( 0 ) of the converted iris image in the polar coordinates, 20 arrays of image information from Array( 0 ) to Array( ⁇ 10 ) and from Array( 0 ) to Array( 10 ) are temporarily generated.
  • a wavelet transform is performed.
  • the respective characteristic vectors generated by the wavelet transform are compared with previously registered characteristic vectors to obtain similarities.
  • a characteristic vector corresponding to the maximum similarity among the obtained similarities is accepted as the characteristic vector of the user.
  • the characteristic vectors f T (n) of the iris corresponding to the temporarily generated plurality of arrays Array(n) of the iris image are then generated.
  • the characteristic vectors f T (n) are generated from f T ( 0 ) to f T ( 10 ) and from f T ( 0 ) to f T ( ⁇ 10 ).
  • the respective generated characteristic vectors f T (n) are compared with each of the characteristic vectors f R of the enrollees and thus similarities S n are obtained.
  • a characteristic vector f T (n) corresponding to the maximum similarity among the obtained similarities S n is considered the resulting value in which the rotation effect is corrected and accepted as the characteristic vector of the user's iris.
  • the non-contact iris recognition method that is capable of correcting the rotated iris image, there is an advantage in that by detecting the inner and outer boundaries of the iris using the differences in pixels of the Canny edge detector, the boundaries of the iris can be more correctly detected from the eye image of the user. If the iris in the eye image acquired by the image acquisition device has been rotated at an arbitrary angle with respect to the centerline of the iris, the rotated iris image is corrected. In addition, if the lower portion of the converted iris image in the polar coordinates is curved and thus has an irregular shape due to the slanted iris image, the iris image is normalized in predetermined dimensions. Hence, the present invention is capable of enabling a variety of deformations that may occur during the authentication operation into a correct iris image necessary for authentication purposes, so as to greatly reduce both false acceptance and rejection rates.

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US20080159600A1 (en) 2008-07-03
US20040114782A1 (en) 2004-06-17
JP2002269565A (ja) 2002-09-20
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US7298874B2 (en) 2007-11-20
CN1493055A (zh) 2004-04-28
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