KR20220108442A - Method of authorizing identity using an iris and system thereof - Google Patents

Abstract

A user authentication method comprises the steps of: acquiring an encoded pattern by using an authentication device, wherein the encoded pattern includes a structure which indicates data corresponding to a first iris code indicating a first region, which is a portion of an iris image of a first user; generating the first iris code from the encoded pattern; acquiring an iris image of a second user; receiving information related to a position relationship between the first region and the entire iris image of the first user; generating a second iris code from the iris image of the second user, extracting a second region corresponding to the first region from the iris image of the second user by using the information related to the position relationship, and generating the second iris code from the second region; comparing the first iris code with the second iris code; and confirming, on the basis of the comparison result, whether the first user is the same as the second user. The present invention can improve accuracy in iris recognition.

Description

Iris authentication method and iris authentication system {METHOD OF AUTHORIZING IDENTITY USING AN IRIS AND SYSTEM THEREOF}

The present disclosure relates to an iris authentication method and system for acquiring an iris image, comparing it with previously registered information, and determining whether it is the same person. The present invention relates to an iris authentication method and system for generating and using a code corresponding to the extraction of feature information.

In general, in a method of recognizing a specific individual using an iris, iris characteristic information is encoded and stored from an iris image in an image signal obtained by photographing a human eye part, and by comparing a code stored in a database in advance, the comparison result is to authenticate the identity of a specific individual. U.S. Patent No. 5,291,560 of John G. Daugman discloses an iris authentication method.

In the Dogman patent, the circle that best approximates the boundary line between the iris and the pupil is found, the boundary between the iris and the sclera is also approximated with a circle in the same principle, and the area between them is set as the iris area, and this area is set as the isoproportional principle. sets an annular selection area partitioned by a plurality of concentric circles, and builds a database using iris characteristic information extracted through Gabor transformation from each selection area as an iris code. During authentication, the iris characteristic information extracted from the human eye is compared with the registered iris characteristic information for each selected area to authenticate the identity of a specific individual.

The applicant's US Patent No. 6,247,813 discloses that the iris code is extracted from the fibrous tissue of the iris obtained from the iris image, the response of the pupil and autonomic ring to light, the shape of the autonomic ring, and the location and shape of the hiatus, A technology for discriminating a specific individual using this is disclosed.

US Patent No. 8,009,876 of the present applicant divides an iris image into a plurality of regions and selectively merges each unit divided region to generate an iris code from the region to increase iris recognition.

US Patent No. 5,291,560 US Patent No. 6,247,813 US Patent Registration No. 8,009,876

According to the present disclosure, the accuracy of iris recognition may be increased by dividing the iris region into a plurality of regions and extracting an iris code from each region.

According to one aspect of the present disclosure, in a method of generating an iris code from an image of an iris, dividing at least a part of a region between an inner boundary and an outer boundary of the iris into a plurality of divided regions, the region includes a first divided region including at least a portion of the autonomic ring of the iris and a second divided region not including the autonomic ring of the iris; extracting a plurality of first features by applying a first transform to the first divided region and extracting at least one second feature by applying a second transform to the second divided region; and generating an iris code based on the plurality of first characteristics and the at least one second characteristic.

According to an embodiment, the first transform and the second transform may include a wavelet transform, and the decomposition level of the first transform may have an order greater than the decomposition level of the second transform. have.

According to an embodiment, the method may further include dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas.

According to an embodiment, the plurality of divided regions further include a third divided region that does not include the autonomic nerve ring, and the first divided region is adjacent to the second divided region, wherein the second divided region is adjacent to the second divided region. After dividing at least a part of a region located between the first divided region and the third divided region and between the inner boundary and the outer boundary of the iris into a plurality of divided regions, a third transformation is applied to the third divided region. The method may further include extracting at least one third feature, wherein a decomposition level of the first transform may have an order greater than a decomposition level of the third transform.

According to an embodiment, the decomposition level of the second transform may have a higher order than the decomposition level of the third transform.

According to an embodiment, before dividing at least a portion of the area between the inner boundary and the outer boundary of the iris into a plurality of divided areas, at least a portion of the area between the inner boundary and the outer boundary of the iris is divided into a rectangular area. It may further include the step of mapping.

According to an embodiment, after the step of mapping the plurality of divided areas to the rectangular area, the step of further dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas may include more.

According to an embodiment, the step of further dividing the plurality of unit division areas into a plurality of unit division areas includes dividing a portion of the unit division area that is most likely to be covered by the upper eyebrow into a first unit division area, and placing the lower eyebrows in the unit division area. dividing a portion that is likely to be hidden into a second unit divided area, and dividing a portion that is less likely to be covered into a third unit divided area, wherein the size of the first unit divided area < the second unit The size of the divided area < the size of the third unit divided area - may be.

According to an embodiment, the first transform and the second transform include a Haar transform, and the plurality of first features and the at least one second feature include a low frequency component can do.

According to an embodiment, the dividing at least a portion of the region between the inner boundary and the outer boundary of the iris into a plurality of divided regions may further include determining a region in which the autonomic ring is located.

According to an embodiment, the determining of the region in which the autonomic ring is located may include determining the region in which the autonomic ring is located based on a distance from the pupil to the inner boundary and the outer boundary of the iris.

According to another aspect of the present disclosure, there is provided an iris authentication system, comprising: an acquisition module configured to acquire an iris image; Separate the iris region from the iris image, divide the iris region into a plurality of divided regions including a first divided region and a second divided region, and apply a first transform having a first decomposition level to the first divided region to extract a plurality of first features and apply a second transform having a second decomposition level smaller than the first decomposition level to the second partition region to extract at least one second feature, an encoding module for generating an iris code based on a first characteristic and the at least one second characteristic; and a matching module configured to receive and compare the iris code with the iris code from the database, and perform iris authentication based on the comparison result.

According to an embodiment, the first divided area may include an autonomic ring and the second divided area may not include an autonomic ring.

According to an embodiment, the first transform and the second transform include a Haar transform, and the plurality of first features and the at least one second feature include a low frequency component can do.

According to another aspect of the present disclosure, in a method of generating an iris code from an image of an iris, dividing at least a portion of a region between an inner boundary and an outer boundary of the iris into a plurality of divided regions, the region includes a first divided region comprising a first iris pattern of a first density and a second divided region comprising a second iris pattern of a second density less than the first density; extracting a plurality of first features by applying a first transform to the first divided region and extracting at least one second feature by applying a second transform to the second divided region; and generating an iris code based on the plurality of first characteristics and the at least one second characteristic.

According to an embodiment, the first transform and the second transform may include a wavelet transform, and the decomposition level of the first transform may have an order greater than the decomposition level of the second transform. have.

According to another aspect of the present disclosure, there is provided a method for generating an iris code from an image of an iris, the method comprising: converting at least a portion of a region between an inner boundary and an outer boundary of the iris into a rectangular region coordinate system; dividing the region between the inner boundary and the outer boundary of the iris transformed into the rectangular region coordinate system into a plurality of divided regions, wherein the plurality of divided regions include a first divided region in which an autonomic ring is estimated to be located and an autonomic ring includes a second partition that is not supposed to be located; extracting a plurality of first features by applying a first transform to the first partitioned region and extracting at least one second feature by applying a second transform to the second partitioned region, decomposition of the first transform the level has an order greater than the decomposition level of the second transform; and generating an iris code based on the plurality of first features and the at least one second feature.

In an embodiment, the method of generating an iris code from an image of an iris may further include dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas. .

In an embodiment, the first divided region may further include a region in which the pupil sphincter is located, and the second divided region may be a region located outside the first divided region.

By dividing the iris region into a plurality of regions and adding information of various frequency bands to each region, accuracy in iris recognition can be improved.

1 is an example of an image of one eye including the entire iris.
FIG. 2 is an example of an iris image obtained from the image of one eye of FIG. 1 .
3 is an example in which an iris image is divided into a plurality of regions.
4 is an example of dividing an iris region into a plurality of regions.
5 is an example of dividing an iris region into a plurality of regions.
6A to 6C are exemplary diagrams of decomposing an image into a plurality of levels.
7 is an example of a binary tree when a signal is decomposed into three levels.
8A is an example of converting an iris region into a coordinate system of a rectangular region.
8B is a conceptual diagram of wavelet transformation of the rectangular region coordinate system of FIG. 8A.
9A is another example of converting an iris region into a coordinate system of a rectangular region.
9B is a conceptual diagram of wavelet transformation of the rectangular region coordinate system of FIG. 9A.
10 is a conceptual diagram of an iris authentication system according to an embodiment of the present disclosure.
11 is a flowchart of an authentication method according to an embodiment of the present disclosure.

Hereinafter, the present disclosure will be described in detail with reference to the drawings. In describing the present disclosure, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present disclosure, a detailed description thereof will be omitted. In addition, the following examples may be modified in various other forms, and the scope of the technical spirit of the present disclosure is not limited to the following examples. Rather, these embodiments are provided to more fully and complete the present disclosure, and to fully convey the technical spirit of the present disclosure to those skilled in the art.

It is to be understood that the technology described in the present disclosure is not intended to be limited to specific embodiments, and includes various modifications, equivalents, and/or alternatives of the embodiments of the present disclosure.

In connection with the description of the drawings, like reference numerals may be used for like components.

In the present disclosure, expressions such as “have,” “may have,” “include,” or “may include” indicate the presence of a corresponding characteristic (eg, a numerical value, function, operation, or component such as a part). and does not exclude the presence of additional features. In this disclosure, expressions such as “A or B,” “at least one of A and/and B,” or “one or more of A or/and B” may include all possible combinations of the items listed together. . For example, "A or B," "at least one of A and B," or "at least one of A or B" means (1) includes at least one A, (2) includes at least one B; Or (3) it may refer to all cases including both at least one A and at least one B.

As used in the present disclosure, expressions such as “first,” “second,” “first,” or “second,” may modify various elements, regardless of order and/or importance, and refer to one element. It is used only to distinguish it from other components, and does not limit the components.

A component (eg, a first component) is "coupled with/to (operatively or communicatively)" to another component (eg, a second component) When referring to "connected to", it should be understood that the certain element may be directly connected to the other element or may be connected through another element (eg, a third element). On the other hand, when it is said that a component (eg, a first component) is "directly connected" or "directly connected" to another component (eg, a second component), the component and the It may be understood that other components (eg, a third component) do not exist between other components.

The expression "configured to (or configured to)" as used in this disclosure depends on the context, for example, "suitable for," "having the capacity to" ," "designed to," "adapted to," "made to," or "capable of." The term “configured (or configured to)” may not necessarily mean only “specifically designed to” hardware. Instead, in some circumstances, the expression “a device configured to” may mean that the device is “capable of” with other devices or parts. For example, the phrases "a processor configured (or configured to perform) A, B, and C," "a module configured (or configured to perform) A, B, and C," refers to a dedicated processor ( For example, it may refer to an embedded processor) or a generic-purpose processor (eg, a CPU or an application processor) capable of performing corresponding operations by executing one or more software programs stored in a memory device.

U.S. Patent Nos. 5,291,560, 6,247,813, and 8,009,876 are incorporated herein by reference. A portion briefly described in the present disclosure may be substituted with the contents disclosed in U.S. Patent Nos. 5,291,560, 6,247,813, and 8,009,876.

According to an embodiment, authentication using iris recognition detects the iris from an original image of the eye to obtain an iris image, and localizes the iris image to segment the pupil region and the iris region. . The iris region is normalized and transformed into a fixed dimension, and transformed into a rectangular region that can be interpreted in a row and column format. This is also called mapping. An iris code is extracted by encoding the rectangular region. US Patent No. 8,009,876 discloses a method of dividing an iris region into a plurality of various regions using a variable multi-sector method and extracting an iris code from each region. Authentication is performed by comparing the extracted iris code with a previously stored template.

Hereinafter, a method of extracting an iris code from an iris region will be described with reference to the drawings.

1 is an example of an image 100 of a user's eye according to an embodiment. 2 is an enlarged example of an image of a user's pupil.

1 and 2 , an eye image 100 includes a pupil 120 and an iris 110 surrounding the pupil 120 . The iris 110 includes an autonomic nerve wreath 130 . In general, in the iris, the pattern of the iris is formed by the pupil sphincter muscle (not shown), the dilator muscle (not shown), collagenous fiber (not shown), the autonomic nerve ring 130, etc. do. The region where the pupil sphincter and the dilate muscle overlap is also called the iris sphincter or the iris division ring (collarette), and the autonomic ring 130 and the iris division ring are also referred to as the same. In general, there is an autonomic nerve ring 130 at the ⅓ point of the pupil 120 side, and based on this, the pupil sphincter is on the inside, and the dilatation of the pupil on the outside. In general, in the pupil sphincter region, the first fringes (radial furrows, 134) appear complex, and in the dilated pupil region, the second fringes 138 are relatively few. The autonomic nerve ring 130 may be connected to the bakksal 132 . Patterns present in the iris 110 such as the autonomic nerve ring 130 , the rib cage 132 , the first pattern 134 , and the second pattern 138 are also called iris patterns. In FIG. 2 , the first pattern 134 and the second pattern 138 are conceptualized, and the shapes of the actual pupil sphincter (the first pattern) and the pupil dilator muscle 138 may be different from these.

11 is a flowchart of an authentication method according to an embodiment of the present disclosure.

An iris image is acquired (S1110). The iris image may be obtained by localizing and subdividing an image of the eye obtained through a charge-coupled device (CCD) sensor or a complementary metal-oxide semiconductor (CMOS) sensor. The obtained iris image is divided into a plurality of regions (S1120). For example, the boundary between the iris and the sclera may be detected, and the iris region may be divided around the pupil and also divided through radial division. The divided region may include a first divided region including the autonomic ring and a second divided region not including the autonomic ring. The division of the region may use the methods described in the present disclosure and references. A first transform is applied to the first divided region to extract a plurality of first features, and a second transform is applied to the second divided region to extract at least one second feature (S1130). The first transform and the second transform may include a wavelet transform, and a decomposition level of the first transform may have an order greater than a decomposition level of the second transform. An iris code is generated based on the extracted features (S1140).

Segmentation and feature extraction of the iris region will be described in detail below.

3 is an example in which an iris region is divided into a plurality of regions. Although the pupil 120 and the iris 110 are shown as concentric circles for convenience, it is apparent in the art that the actual shape of the pupil 120 and the iris 110 may not be exactly a circle.

Referring to FIG. 3 , the iris region 110 may be divided into an upper portion R1 , a middle portion R2 , and a lower portion R3 of the pupil 120 . In an embodiment, the iris region 110 is divided into a first region C1 , a second region C2 , a third region C3 , and a fourth region C4 in a radial direction with respect to the pupil 120 . can be Here, the radiating regions C1 to C4 divided in the radial direction are exemplary, and the number of regions divided in the radial direction is not limited to four. Each radiation area C1 to C4 may be divided into a plurality of unit division areas.

In an embodiment, the upper part R1 may be an iris region at least partially covered by the upper eyebrow or eyelid. The lower portion R3 may be an iris region at least partially covered by the lower eyebrows or eyelids. In one embodiment, the upper portion R1 may be about 60% of the distance from the center of the pupil 120 or the center of the iris 110 to the outer boundary of the iris 110 . The lower portion R3 may be about 40% of the distance from the center of the pupil 120 to the outer boundary of the iris 110 . In one embodiment, the upper part R1 and the lower part R3 may not include the autonomic ring 130 . In the process of mapping the region of the iris 110 , accurate iris coordinates (center, distance to the iris outer boundary) and pupil coordinates (center, distance to the pupil boundary) may be used.

In the human eye, in reality the center of the pupil and the center of the iris are not completely coincident and are in similar positions. Since the pupil and the center of the iris can be roughly regarded as being substantially the same, in this specification, the center of the pupil may actually mean the center of the iris.

4 is an example of dividing an iris region into a plurality of regions. In FIG. 4, the pattern of the iris is omitted. By mapping the iris region, the region division shown in FIG. 5(b) of US Patent No. 8,009,876 can be obtained. A detailed description is disclosed in U.S. Patent No. 8,009,876 and is incorporated herein by reference. Region division will be further described later in this specification.

Referring to FIG. 4 , the size of the unit division region included in the upper part R1 close to the upper eyebrow may be smaller than the size of the unit division region included in the lower part R3 close to the lower eyebrow. In an embodiment, the size S11 of the at least one unit divided area included in the upper part R1 may be smaller than the size S21 of the at least one unit divided area included in the lower part R3. The size S21 of the at least one unit division area included in the lower part R3 may be smaller than the sizes S31 , S32 , S33 , and S34 of the at least one unit division area of the middle part R2 .

In an embodiment, the size of the unit division region may increase toward the inner side of the iris. For example, in the upper part R1 , the size S11 of the unit division region located outside the iris 110 may be smaller than the size S12 of the unit division region located inside the iris 110 . In the lower portion R3 , the size S21 of the unit division region located outside the iris 110 may be smaller than the size S22 of the unit division region located inside the iris 110 . In another embodiment, the size of the unit division region may vary according to the pattern density of the iris 110 . For example, a transform with a higher order of decomposition level may be applied to a dense region.

5 is an example of dividing an iris region into a plurality of unit division regions. In FIG. 5, the iris pattern is omitted. In addition, only a part of the unit division area is shown in FIG. 5 for explanation. As shown in FIG. 3 , the iris region 110 is divided into a first region C1 , a second region C2 , a third region C3 , and a fourth region C4 in the radial direction with respect to the pupil 120 . can be Here, the radiating regions C1 to C4 divided in the radial direction are exemplary, and the number of regions divided in the radial direction is not limited to four. For convenience of explanation, the second region C2 has been illustrated to include the autonomic nerve ring 130 and the baqusal 132 , but the positions of the autonomic neural ring 130 and the baqusal 132 are not limited thereto. For example, the autonomic nerve ring 130 and/or the hippocampus 132 may be positioned to span at least two of the first to fourth regions.

In one embodiment, the mapping calculates the coordinate values (center, distance to the boundary line) of the corresponding figure by obtaining the closest circle or ellipse for each of the iris 110 and the pupil 120, and polar coordinates mapping ), the donut-shaped iris region can be collectively converted into a rectangular shape.

In an embodiment, the iris region 110 may be mapped in a rectangular coordinate system, and then, radial direction division and unit area division may be performed.

In an embodiment, after the iris region 110 is divided in a radial direction with the pupil 120 as the center, the iris region 110 may be mapped in a rectangular coordinate system, and then divided into unit division regions.

In an embodiment, the iris region 110 may be divided in a radial direction with the pupil 120 as a center, divided into unit division regions, and then mapped in a rectangular coordinate system.

An iris code is extracted from the divided unit division area. Various wavelet transforms are available for iris code extraction. In the present disclosure, the Haar transform is described as an example, but the wavelet transform is not limited to the Haar transform.

In the present disclosure, when the iris code is extracted, it may be decomposed into different levels according to the iris pattern included in the unit divided region (or divided region).

In an embodiment, different levels of wavelet transform may be applied according to the density of the iris pattern. For example, to apply a wavelet transform with a relatively high decomposition level to regions with (relatively) high density of iris patterns, and apply a wavelet transform with a relatively low decomposition level to regions with (relatively) low density of iris patterns. can

In an embodiment, the region having a high density of the iris pattern may include a region in which the autonomic ring 130 is located. Since the location of the region where the autonomic ring 130 exists may be different for each person, the area where the autonomic ring is located is estimated, and the area between the inner and outer boundaries of the iris is the area where the autonomic ring is estimated to be located. It can be divided into regions where the autonomic ring is not presumed to be located. In general, it can be estimated that the autonomic nerve ring 130 is located at the ⅓ point on the pupil 120 side. Alternatively, as shown in FIG. 5 , based on the distance to the inner boundary and the outer boundary of the iris region 110 , it is estimated that the autonomic ring 130 is located and the area where the autonomic ring 130 is not located. area can be divided.

In an embodiment, the dense region of the iris pattern may include a region in which the pupil sphincter 134 is present. Alternatively, the region in which the density of the iris pattern is high may include a region in which the autonomic nerve ring 130 and the pupil sphincter 134 are located. For example, the pupil sphincter 134 may be located in the C1 region. That is, the decomposition level of the wavelet transform applied to the region where the autonomic ring 130 and/or the pupil sphincter 134 is located or the region where it is estimated to be located (region C1 and/or C2) is the autonomic ring 130) and/or the pupil. It may be relatively higher than the decomposition level of the wavelet transform applied to the region where the sphincter 134 is located or the region C3 and/or C4 that is estimated not to be located.

When the Haar transform is used as the wavelet transform, the unit divided region may be decomposed into different levels according to the iris pattern included in the divided region. Accordingly, it is possible to increase the matching success rate for the iris region that is deformed in various sizes according to lighting conditions. In an exemplary embodiment, the decomposition level applied when converting the divided region C21 in which the autonomic ring 130 is located and the divided regions C31 and C41 in which the autonomic ring 130 is not located may be different. For example, the decomposition level of the transformation applied to the segmented region C21 in which the autonomic ring 130 is located is of an order greater than the decomposition level applied to the segmented regions C31 and C41 in which the autonomic ring 130 is not located. ) can have In addition, as the distance from the divided region C21 in which the autonomic ring 130 is located increases, the order of the decomposition level may decrease.

In one embodiment, the region in which the autonomic nerve ring 130 of the iris and/or at least a portion of the pupil sphincter is located may be preset. By localizing the iris image, the pupil region and the iris region may be segmented, and a preset location region of the autonomic ring 130 and/or the pupil sphincter may be determined from the segmented iris region. The iris region is collectively divided into a plurality of divided regions according to a given rule, and the region containing (or likely to be included) the autonomic ring 130 and/or the pupil sphincter is divided into the autonomic ring 130 and/or the pupil sphincter. It can be set to the location where it exists.

For example, if the distance from the inner boundary of the iris 110 to the outer boundary of the region where the autonomic ring 130 is located is D, the region where the autonomic ring 130 is located is defined from the inner boundary of the iris 110 . A region having a distance of 20% (D1) or more of D and a region having a distance (D2) of 40% or less of D from the outer boundary may be set as regions excluding from the iris 110 . The region in which the pupil sphincter is located may include a region having a distance D1 within 20% from the inner boundary of the iris 110 . These figures may vary due to individual differences.

6A to 6C are exemplary diagrams of decomposing an image into a plurality of levels. The wavelet transform or Haar transform uses various wavelet functions as a base function, and analyzes a signal by scaling and shifting the wavelet base function. The larger the scale value, the lower the frequency characteristic, and the smaller the scale value, the higher the frequency characteristic. Accordingly, the signal can be decomposed into an approximate component and a detail component. In this case, the approximate value is the low frequency component and the detailed value is the high frequency component. An approximate value is also called a vector of an approximate coefficient, and a detailed value is also called a vector of a detail coefficient. In iris authentication, an iris code is generated and stored by featuring a low-frequency component. For example, the low frequency component may be stored as the iris code, or the iris code may be generated based on the low frequency component.

6A is an exemplary diagram in which a two-dimensional image is decomposed into a first level using wavelet transform. LL ₁ represents approximate values, and HL ₁ , LH ₁ and HH ₁ represent detailed values. FIG. 6B is an exemplary diagram in which LL ₁ of FIG. 6A is decomposed one more time (second level) using wavelet transform. LL ₂ represents approximate values, and HL ₂ , LH ₂ and HH ₂ represent detailed values. FIG. 6C is an exemplary diagram in which LL ₂ of FIG. 6B is decomposed one more time (third level) using wavelet transform. LL ₃ represents approximate values, and HL ₃ , LH ₃ and HH ₃ represent detailed values. It has been described above that the approximate value is the low-frequency component and the detailed value is the high-frequency component. From this, it can be seen that as the wavelet transform is repeated (as the decomposition level increases or the decomposition order increases), more feature values can be extracted.

7 is an example of a binary tree when the signal S is decomposed into three levels. Referring to FIG. 7 , the signal S is decomposed into a first level approximation A ₁ and a first level detail D ₁ . The first level approximation A ₁ is decomposed into a second level approximation AA ₂ and a second level detail DA ₂ . The second level approximation AA ₂ is decomposed into a third level approximation AAA ₃ and a third level detail DAA ₃ . From this, it can be seen that if the signal is decomposed into three levels, three low-frequency components can be obtained.

As can be seen from FIGS. 6A to 6C and 7 , as the decomposition level increases, more approximations (low frequency components) can be obtained.

8A is an example of converting an iris region into a coordinate system of a rectangular region. 8B is a conceptual diagram of wavelet transformation of the rectangular region coordinate system of FIG. 8A. In FIG. 8A , the iris pattern is omitted for convenience. In FIG. 8B, for convenience, only the leftmost unit divided regions D1, ANW1, B1, and A1 are shown by wavelet transformation.

Referring to FIG. 8A , regions C1', C2', C3' and C4' are in the first region C1, the second region C2, the third region C3, and the fourth region C4 of FIG. 5 . each corresponds to It is assumed that the autonomic ring 130 (see FIG. 3) is located in the C2' region and the autonomic ring is not located in the C1', C3', and C4' regions. A wavelet transform is applied with different decomposition level orders to the unit divided regions D1, ANW1, B1, A1 of the regions C1', C2', C3' and C4'.

In one embodiment, the deepest or most decomposition level is applied to the unit divided region ANW1 of the C2' region where the autonomic ring is located. A decomposition level different from that of the unit division area (ANW1) of the region C2' where the autonomic ring is located can be applied to the unit division regions (D1, B1, A1) of the regions (C1', C3', C4') that do not include the autonomic ring. can

In one embodiment, the level of decomposition may vary depending on the distance from the autonomic ring. For example, the level of degradation may decrease with distance from the autonomic ring. As shown in FIG. 8B , when the unit division region ANW1 of the region C2′ where the autonomic ring is located is decomposed into three levels, the unit division region of regions C1′ and C3′ immediately adjacent to the region C2′ where the autonomic ring is located. (D1, B1) can be decomposed into two levels, and the unit divided area A1 of the region C4' can be decomposed into one level. Here, the orders 1, 2, and 3 of the levels are exemplary for description, and the orders of the levels are not limited thereto. In an embodiment, the decomposition levels applied to the unit divided areas D1, B1, and A1 excluding the unit divided area ANW1 of the C2' area may be different or the same. In addition, the same decomposition level may be applied to each of the adjacent unit division areas D1 , D2/ANW1 , ANW2/B1 , B2/A1 , and A2 of the first to fourth areas C′1 to C4 , or different decomposition levels This may apply.

Alternatively, although not shown, in one embodiment, the decomposition level of the C1' and C3' regions immediately adjacent to the C2' region where the autonomic ring is located may be the same as the decomposition level of the C4' region.

9A is another example of converting an iris region into a coordinate system of a rectangular region. 9B is a conceptual diagram of wavelet transformation of the rectangular region coordinate system of FIG. 9A. In FIG. 9A , the iris pattern is omitted for convenience. Referring to FIG. 9A , regions C1', C2', C3' and C4' are in the first region C1, the second region C2, the third region C3, and the fourth region C4 of FIG. 5 . each corresponds to It is assumed that the autonomic ring 130 (see FIG. 3) is located in the C2' region and the autonomic ring is not located in the C1', C3', and C4' regions. The wavelet transform may be applied to the regions C1', C2', C3', and C4' with different decomposition levels without dividing the regions C1', C2', C3', and C4' into a plurality of unit divided regions.

In one embodiment, the deepest or most decomposition level is applied to the unit divided region (ANW) of the C2' region where the autonomic ring is located. A decomposition level different from that of the C2' region in which the autonomic ring is located can be applied to the regions (C1', C3', C4') that do not include the autonomic ring. As shown in Fig. 9b, when the region C2' where the autonomic ring is located is decomposed into 3 levels, the regions C1' and C3' immediately adjacent to the region C2' where the autonomic ring is located are decomposed into 2 levels, and the region C4' is It can be disassembled to level 1. Alternatively, the same decomposition level may be applied to the regions (C1', C3', C4') that do not include the autonomic ring.

In one embodiment, a combination of FIGS. 8A and 9A is also possible. For example, the region C2' in which the autonomic ring is located may not be divided, and at least one of C1', C3', and C4' may be divided into unit division regions.

In an embodiment, as shown in FIG. 8A , the first to fourth regions C1 to C4 are converted into a rectangular coordinate system, and then, as shown in FIG. 9A , the regions C1', C2', C3' and C4' are divided into a plurality of units. It can be divided into partitions.

Referring back to FIG. 7 , the low frequency component varies according to the division level. For example, when the image is decomposed into three levels as shown in FIG. 7 , three low-frequency components (A ₁ , AA ₂ , AAA ₃ ) are generated. An iris code may be generated and used based on the generated low-frequency component. Accordingly, it can be seen that different numbers of low-frequency components can be extracted and different iris codes can be generated according to the decomposition level applied to each divided region. In an embodiment, each of the iris region or segmented region in which the autonomic ring is located may be decomposed to have more low-frequency components than the iris region or segmented region in which the autonomic ring is not located. The low-frequency component (or iris code generated based on the low-frequency component) extracted from the iris region or segmented region where the autonomic ring is located can be used as a feature in a subsequent matching process.

10 is a conceptual diagram of an iris authentication system 1000 according to an embodiment of the present disclosure. The iris authentication system 1000 includes an acquisition module 1010 , a segmentation module 1020 , a normalization module 1030 , a division module 1035 , and an encoding module 1040 . ) and a matching module 1050 . The iris authentication system 1000 may further include a database 1060 . The iris authentication system 1000 is configured to perform iris authentication using the methods described in this disclosure and references.

The acquiring module 1010 is configured to acquire an image of the eye. The segmentation module 1020 is configured to detect the iris from the eye image to obtain an iris image, and to localize the iris image to distinguish the pupil region and the iris region. The normalization module 1030 is configured to transform the subdivided iris region into a rectangular region interpretable in a row and column format by applying a geometric normalization scheme. The dividing module 1035 is configured to divide the iris region into a plurality of divided regions and/or unit divided regions or divide a rectangular region into a plurality of divided regions and/or unit divided regions. The encoding module 1040 is configured to extract features from the iris region transformed into a rectangular region, the segmented region, and/or the unit segmented region using the feature extraction rule, and generate an iris code. The encoding module 1040 may transmit the generated iris code to the database 1060 . The matching module 1050 is configured to receive the iris code from the database 1060 and match the iris code generated by the encoding module. The matching module 1050 determines iris authentication based on the matching result. The database 1060 is configured to store the iris code and send the iris code to the matching module 1050 .

The apparatus and method described above may be implemented as a hardware component, a software component, and/or a combination of the hardware component and the software component. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or device, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to a person skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floppy disks. -magneto-optical media, and specially configured to store and carry out program instructions such as ROM, RAM, flash memory, etc.

Hardware devices are included. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

An iris feature is extracted by applying a transform of different order to a region with a large number of iris patterns and a region with a small number of iris patterns. Accordingly, it is possible to provide an iris authentication method and system in which discrimination of iris recognition is improved.

100: eye image 110: iris
120: pupil 130: autonomic nervous system
1010: Acquisition module 1020: Segmentation module
1030: regularization module 1035: segmentation module
1040: encoding module 1050: matching module
1060: database

Claims (20)

A method of generating an iris code from an image of an iris, the method comprising:
dividing at least a portion of a region between an inner boundary and an outer boundary of the iris into a plurality of divided regions, wherein the plurality of divided regions include a first divided region including at least a portion of an autonomic ring of the iris and the autonomic ring including a second partitioned area that does not include;
extracting a plurality of first features by applying a first transform to the first divided region and extracting at least one second feature by applying a second transform to the second divided region; and
and generating an iris code based on the plurality of first characteristics and the at least one second characteristic. According to claim 1,
wherein the first transform and the second transform comprise a wavelet transform, wherein a decomposition level of the first transform has an order greater than a decomposition level of the second transform. . According to claim 1,
The method of generating an iris code, further comprising: further dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas. According to claim 1,
The plurality of divided regions may further include a third divided region that does not include the autonomic nerve ring, wherein the first divided region is adjacent to the second divided region, wherein the second divided region includes the first divided region and the second divided region. Located between 3 partitions,
After dividing at least a portion of a region between an inner boundary and an outer boundary of the iris into a plurality of divided regions, the method further includes extracting at least one third feature by applying a third transform to the third divided region. do,
and the decomposition level of the first transform has an order greater than the decomposition level of the third transform. 5. The method of claim 4,
and the decomposition level of the second transform has an order greater than the decomposition level of the third transform. According to claim 1,
Before dividing at least a part of the region between the inner boundary and the outer boundary of the iris into a plurality of divided regions,
and mapping at least a portion of an area between an inner boundary and an outer boundary of the iris to a rectangular area. 7. The method of claim 6,
After the step of mapping the plurality of divided regions to a rectangular region,
The method of generating an iris code, further comprising: further dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas. 8. The method of claim 7,
The step of further dividing into the plurality of unit division regions,
A portion of the unit division area that is relatively likely to be covered by the upper eyebrow is divided into a first unit division area, and a portion of the unit division area that is likely to be covered by the lower eyebrow is divided into a second unit division area, , dividing a portion with a relatively small probability of being covered into a third unit divided area, wherein: the size of the first unit divided area < the size of the second unit divided area < the size of the third unit divided area - How to generate iris code, which is. According to claim 1,
wherein the first transform and the second transform comprise a Haar transform, wherein the plurality of first features and the at least one second feature comprise a low frequency component. How to. According to claim 1,
The dividing at least a portion of the region between the inner boundary and the outer boundary of the iris into a plurality of divided regions further comprises determining a region in which the autonomic ring is located. 11. The method of claim 10,
The step of determining the region in which the autonomic ring is located
A method for generating an iris code, wherein the region in which the autonomic ring is located is determined based on the distance from the pupil to the medial and lateral boundaries of the iris. In the iris authentication system,
an acquisition module configured to acquire an iris image;
a segmentation module configured to distinguish an iris region from an iris image;
a division module configured to divide the iris region into a plurality of divided regions including a first divided region and a second divided region;
A second transform that extracts a plurality of first features by applying a first transform having a first decomposition level to the first partitioned region and has a second decomposition level of an order smaller than the first decomposition level in the second partitioned region an encoding module for extracting at least one second feature by applying , and generating an iris code based on the plurality of first features and the at least one second feature; and
and a matching module configured to receive and compare the iris code with the iris code from a database, and perform iris authentication based on a comparison result. 13. The method of claim 12,
The first divided region includes an autonomic ring and the second divided region does not include an autonomic ring. 13. The method of claim 12,
wherein the first transform and the second transform comprise a Haar transform, and wherein the plurality of first features and the at least one second feature comprise a low frequency component. 13. The method of claim 12,
Further comprising a normalization module (normalization module) for converting the iris region into a rectangular region interpretable in a row and column format,
The dividing module divides the rectangular module into the plurality of divided regions, the iris authentication system. A method of generating an iris code from an image of an iris, the method comprising:
dividing at least a portion of a region between an inner boundary and an outer boundary of the iris into a plurality of divided regions, wherein the plurality of divided regions includes a first divided region including a first iris pattern of a first density and the first a second divided region comprising a second iris pattern of a second density less than the density;
extracting a plurality of first features by applying a first transform to the first divided region and extracting at least one second feature by applying a second transform to the second divided region; and
and generating an iris code based on the plurality of first characteristics and the at least one second characteristic. 17. The method of claim 16,
wherein the first transform and the second transform comprise a wavelet transform, wherein a decomposition level of the first transform has an order greater than a decomposition level of the second transform. . A method of generating an iris code from an image of an iris, the method comprising:
converting at least a portion of an area between the inner boundary and the outer boundary of the iris into a rectangular area coordinate system;
dividing the region between the inner boundary and the outer boundary of the iris transformed into the rectangular region coordinate system into a plurality of divided regions, wherein the plurality of divided regions include a first divided region in which the autonomic ring is estimated to be located and the autonomic ring includes a second partition that is not supposed to be located;
extracting a plurality of first features by applying a first transform to the first partitioned region and extracting at least one second feature by applying a second transform to the second partitioned region; decomposition of the first transform the level has an order greater than the decomposition level of the second transform; and
and generating an iris code based on the plurality of first characteristics and the at least one second characteristic. 19. The method of claim 18,
The method of generating an iris code, further comprising: further dividing at least one of the first divided area and the second divided area into a plurality of unit divided areas. 19. The method of claim 18,
The method of generating an iris code, wherein the first divided region further includes a region in which a pupil sphincter is located and the second divided region is located outside the first divided region.

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