US20190005301A1 - Vascular pattern detection systems - Google Patents
Vascular pattern detection systems Download PDFInfo
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- US20190005301A1 US20190005301A1 US16/109,716 US201816109716A US2019005301A1 US 20190005301 A1 US20190005301 A1 US 20190005301A1 US 201816109716 A US201816109716 A US 201816109716A US 2019005301 A1 US2019005301 A1 US 2019005301A1
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- 238000001514 detection method Methods 0.000 title claims abstract description 66
- 210000004204 blood vessel Anatomy 0.000 claims abstract description 28
- 238000003909 pattern recognition Methods 0.000 claims abstract description 26
- 238000000034 method Methods 0.000 claims abstract description 8
- 125000006850 spacer group Chemical group 0.000 claims description 16
- 238000004891 communication Methods 0.000 claims description 3
- 230000000295 complement effect Effects 0.000 claims description 2
- 229910044991 metal oxide Inorganic materials 0.000 claims description 2
- 150000004706 metal oxides Chemical class 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- 239000004065 semiconductor Substances 0.000 claims description 2
- 239000010409 thin film Substances 0.000 claims description 2
- 238000003491 array Methods 0.000 description 6
- 238000013475 authorization Methods 0.000 description 2
- 239000010408 film Substances 0.000 description 2
- 229910001218 Gallium arsenide Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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- G06—COMPUTING; CALCULATING OR 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
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- G06K9/00013—
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- 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
- G06V10/145—Illumination specially adapted for pattern recognition, e.g. using gratings
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- G—PHYSICS
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
- G06V10/955—Hardware or software architectures specially adapted for image or video understanding using specific electronic processors
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- G—PHYSICS
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- 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
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
- G06V40/1388—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/14—Vascular patterns
Definitions
- PIN personal identification number
- password a password for authentication purposes.
- PINs and passwords can be hacked and are widely regarded as the weakest link in security for these cards.
- FIG. 1A depicts an example portable card that includes a vascular pattern recognition system as described herein.
- FIG. 1B-1E depict examples of vascular pattern recognition systems.
- FIG. 2A depicts a top view of an example detection region on a portable card used with a vascular pattern recognition system.
- FIG. 2B depicts a side view of an example vascular pattern detection system.
- FIG. 3A depicts a top view of an example detection region on a portable card used with a vascular pattern recognition system.
- FIG. 3B depicts a side view of another example vascular pattern detection system.
- FIG. 4A depicts a side view of an example vascular pattern detection system.
- FIG. 4B depicts an isometric view of an example vascular pattern detection system.
- FIG. 5A depicts a side view of an example vascular pattern detection system.
- FIG. 5B depicts a top view of an example vascular pattern detection system.
- Vascular pattern recognition is a highly secure biometric authentication method that uses the unique blood vessel patterns in a user's finger or palm as a means of identification. An image of the user's blood vessels may be pre-registered and stored for comparison at a later time to a real-time image of the living blood vessels of the user to identify the user. Because living blood vessels are used for user authentication, it would be extremely difficult to deceive a vascular pattern recognition system. While vascular pattern recognition systems have been used to authenticate a user's identity, known systems are expensive and bulky.
- vascular pattern recognition systems for portable secure cards, such as credit cards and smart badges, having a thickness of less than approximately two millimeters.
- the system uses flexible hybrid electronics and photonics technology to integrate a compact finger vascular pattern detection and authentication system on the card, resulting in a card that provides enhanced security protection compared to personal identification number (PIN) or signature security systems.
- PIN personal identification number
- FIG. 1A depicts an example portable card 100 that includes a vascular pattern recognition system 120 .
- the portable card 100 may be a secure card used in conjunction with an authentication and authorization system, such as may be used with a credit card or smart badge.
- the vascular pattern recognition system 120 may communicate with a card reader (not shown) contactlessly via a near field communication (NFC) antenna 130 or using a contact method via a smart chip 140 . Communications from the vascular pattern recognition system 120 to the card reader may include an authorization code upon confirmation of the identity of the user of the portable card 100 based on the user's finger vascular pattern.
- the portable card 100 is thin, having a thickness of approximately two millimeters or less. Further, the vascular pattern recognition system 120 integrated on the portable card 100 also has a thickness of approximately two millimeters or less. In some implementations, the vascular pattern recognition system may have an area on the portable card 100 that is approximately 25 ⁇ 30 mm 2 or smaller.
- a vascular pattern recognition system 120 may include a vascular pattern detection system 125 , an image processor 162 and a security processor 164 .
- the vascular pattern detection system 125 can obtain image data of blood vessels of a finger to be swiped across a detection area on the portable card.
- the vascular pattern detection system 125 may include a near infrared (NIR) light source 152 and an image sensor array 154 .
- the light source 152 should emit in the NIR, within a wavelength range of approximately 800 nm to 1000 nm. At these wavelengths, the light is transmitted through human tissue, ie, the skin, but is absorbed and scattered by the blood in the blood vessels.
- the light source 152 may be light-emitting diodes (LEDs), such as GaAs and organic LEDs, which can emit light in the NIR wavelength range.
- the image sensor array 154 may be a complementary metal-oxide semiconductor (CMOS) image sensor array, and in other implementations, the image sensor array 154 may be a printed thin-film transistor-based photodiode image sensor array.
- CMOS complementary metal-oxide semiconductor
- the image processor 162 processes the image data obtained by the vascular pattern detection system 125 to generate a scanned vascular pattern.
- the image sensor array 154 may have a length smaller than a length of a person's fingertip where the vascular pattern is located because a smaller image sensor array 154 is more cost effective.
- the width of the image sensor array 154 may be approximately an adult finger width across, approximately 2-3 cm, while the length of the image sensor array 154 may be shorter than the width.
- the obtained image data may include a series of images of the finger's vascular pattern, and the image processor 162 may use an image stitching algorithm on the series of images to stitch together the scanned images to generate a scanned vascular pattern.
- a similar stitching algorithm is used for scanning finger fingerprints.
- the image processor 162 compares the scanned vascular pattern, which may be a stitched vascular pattern, to a pre-stored pattern stored in a memory location on the portable card to authenticate the image data.
- Scanned vascular pattern data may include relative locations of blood vessel branching points, blood vessel thickness, and blood vessel branching angles.
- the pre-stored pattern may be a pre-registered image data of a vascular pattern of an authorized user.
- the security processor 164 generates a transaction or authentication code to authorize a transaction upon authentication of the image data, where the transaction code is transmitted through a contact method with a card reader or contactlessly via NFC.
- the vascular pattern detection system 125 , the image processor 162 , and the security processor 164 may be implemented using a one-chip or a two-chip system.
- a one-chip system may be beneficial because the elements on the chip may be integrated together into a smaller area, providing a reduction in a lower cost design.
- a two-chip system may have a different benefit, where the financial institution that issues the card, such as a credit card issuer, may generate its own security chip with a security processor, and the non-secure portion, such as the vascular pattern detection system 125 , may be manufactured by a different manufacturer.
- FIG. 1C-1E depict examples of vascular pattern recognition systems 120 .
- FIG. 1C depicts an example of a two-chip system where the vascular pattern detection system 125 and the image processor 162 are part of a first chip 171 on the portable card, and the security processor 164 is part of a second chip 172 on the portable card.
- the pre-stored pattern 166 may be stored on the first chip 171 .
- the first chip 171 and the second chip 172 are distinct and communicatively coupled.
- the image processor 162 processes the image data obtained by the vascular pattern detection system 125 , and the image processor 162 sends an indication of authentication of the image data to the security processor 164 .
- the security processor 164 may generate a transaction code.
- FIG. 1D depicts an example of a two-chip system where the vascular pattern detection system 125 is part of a first chip 173 on the portable card, and the security processor 164 and the image processor 162 are part of a second chip 174 on the portable card.
- the pre-stored pattern 166 may be stored on the second chip 174 .
- the first chip 173 and the second chip 174 are distinct and communicatively coupled.
- the image data obtained by the vascular pattern detection system 125 is transmitted to the image processor 162 for processing, and the image processor 162 sends an indication of authentication of the image data to the security processor 164 .
- FIG. 1E depicts an example of a one-chip system where the vascular pattern detection system 125 , the image processor 162 , and the security processor 164 are part of a single chip 175 on the portable card, and the pre-stored pattern 166 is stored on the single chip 175 .
- the image processor 162 processes the image data obtained by the vascular pattern detection system 125 , and the image processor 162 sends an indication of authentication of the image data to the security processor 164 .
- FIGS. 2A and 3A each show a top view of examples of detection regions 220 , 320 on a portable card to be used with a vascular pattern detection system.
- the detection region 220 , 320 may be a recessed region.
- a user's finger 210 is to be swiped across a length of the detection region 220 , 320 such that a vascular pattern of the finger's blood vessels 212 may be detected and authenticated by the vascular pattern recognition system.
- the detection region 220 is round, having a diameter approximately a finger's width across.
- the recessed region may have a first sloping edge 221 along the width on a first side and a second sloping edge 223 along the width on a second side opposite the first side.
- the detection region 320 is square, where the length of each side is approximately a finger's width across.
- the detection region 220 , 320 may be any shape and size, such as a rectangle having a width approximately a finger's width across and a length shorter than the width.
- FIGS. 2B and 3B each show a side view of a vascular pattern detection system based on lateral placement of a NIR light source and an image sensor array.
- FIG. 2B depicts a side view of an example vascular pattern detection system that includes a first NIR LED array 222 positioned along the first sloping edge 221 and an image sensor array 224 to receive light emitted by the first NIR LED array (representative solid line ray 222 a ) and scattered (representative dotted line rays 222 b ) from blood vessels of a finger to be swiped along the length of the recessed region 220 .
- the image sensor array 224 is positioned on the second sloping edge 223 of the recessed region, as shown in the example of FIG. 2B .
- the image sensor array 224 may be positioned, as shown in the example of FIG. 3B , where an example vascular pattern detection system includes a recessed region 320 .
- a first NIR LED array 330 is positioned along the first sloping edge 331 of the recessed region 320
- an image sensor array 224 is positioned at a bottom 333 of the recessed region 320 to receive light emitted by the first NIR LED array (representative ray 330 a ) and scattered (representative rays 330 b ) from blood vessels of a finger to be swiped along the length of the recessed region 320 .
- a second NIR LED array 334 may be positioned along a second sloping edge 332 of the recessed region 320 , where the image sensor array 224 further receives light emitted by the second NIR LED 334 array and scattered from the blood vessels of the finger 210 .
- the recessed region 320 may have other NIR LED arrays around the perimeter to illuminate the finger 320 to be swiped across the recess region 320 .
- a NIR filter and spacer 226 may be positioned over the image sensor array 224 , and a microlens array 228 may be positioned over the NIR filter and spacer 226 .
- the NIR filter and spacer 226 blocks wavelengths of light that are not within the range of wavelengths emitted by the NIR LED arrays 222 , 330 , 334 because the image sensor array 224 is sensitive to other wavelengths of light, such as ambient light, that may interfere with the desired image data of the vascular pattern to be detected.
- the NIR filter and spacer 226 provides a pre-defined focusing distance between the microlenses in the microlens array 228 and the pixels of the image sensor array 224 , as shown by the representative rays 351 , 352 in the example of FIG. 3B .
- FIGS. 4A and 5A each depict a side view of an example vascular pattern detection system based on vertical placement of a NIR light source and an image sensor array.
- FIG. 4A depicts a side view of an example vascular pattern detection system that includes a scanning area having a width approximately a finger's width across and a length 401 that may be shorter than the width.
- the vascular pattern detection system also includes an image sensor array 224 within the scanning area.
- a NIR filter and spacer 226 is positioned over the image sensor array 224
- a microlens array 228 is positioned over the NIR filter and spacer 226 .
- NIR light source to emit light above the microlens array 228 toward a finger 210 to be swiped along the length of the scanning area, where the image sensor array 224 receives light emitted by the NIR light source and scattered from blood vessels 212 of the finger 210 .
- the NIR light source includes an edge emitting LED 410 and a light guide 420 positioned over a portion of the microlens array 228 , where light emitted by the edge emitting LED 410 (representative rays 412 ) couples into the light guide 420 and travels along the light guide 420 via total internal reflection.
- there may be multiple light guides 420 such as shown in the example of FIG. 4B , an isometric view of the example vascular pattern detection system.
- light scatterers 440 are positioned outside the light guide 420 on a first surface closest to the microlens array 228 to scatter light (representative ray 413 ) in the light guide 420 toward the finger 210 , where the light scatterers 440 are positioned around a first pinhole array 461 on a surface of the light guide 420 closer to the image sensor array 224 than the finger 210 .
- a second pinhole array 462 may be positioned on an opposite surface of the light guide 420 , closer to where the finger 210 may be swiped across the scanning area.
- the second pinhole array 462 is aligned with the first pinhole array 461 , such that the aligned pinhole arrays 461 , 462 direct light scattered from the blood vessels 212 (representative dotted line rays 416 ) to pixels of the image sensor array 224 (representative rays 418 ).
- pinhole arrays 462 , 461 may be interleaved with light guides 420 to allow light from the various light guides 420 to be directed to the pixels of the image sensor array 224 .
- angle sensitive data may be derived from the light received by the image sensor array 224 and used to generate a three-dimensional image of the blood vessels of the finger, not merely a two-dimensional image.
- a diffuser layer 430 is positioned between the emitted light 412 from the NIR light source and the finger 210 to be scanned.
- the diffuser layer 430 collimates light from the light scatterers 440 (representative rays 414 ), and the diffuser layer 430 is positioned around the second pinhole array 462 .
- a reflection film 450 may be adhered to a surface of the light scatterers 440 away from the light guide 420 .
- the reflection film 450 is a polarized reflecting plane that transmits light from the vertical direction while reflecting light from other directions. As a result, light is scattered in all directions from the light scatterers 440 toward the finger, while light traveling vertically downward 224 from the blood vessel 212 is permitted to pass through to the image sensor array 224 .
- FIG. 5A depicts a side view of an example vascular pattern detection system. Similar to FIG. 4A , the vascular pattern detection system includes a scanning area having a width approximately a finger's width across and a length 501 that may be shorter than the width. As with the other example vascular detect systems, the vascular pattern detection system also includes an image sensor array 224 within the scanning area, a NIR filter and spacer 226 positioned over the image sensor array 224 , and a microlens array 228 positioned over the NIR filter and spacer 226 .
- the NIR light source that emits light above the microlens array 228 toward a finger 210 to be swiped along the length of the scanning area may be an organic light-emitting diode (OLED) array 510 positioned above the microlens array 228 .
- OLED organic light-emitting diode
- the OLED array 510 emits light (representative solid line rays 512 ) directly upward toward the finger 210 to be swiped across the scanning area, and the light is scattered (representative dotted line rays) from blood vessels 212 of the finger 210 to the image sensor array 224 .
- FIG. 5B depicts a top view of the example vascular pattern detection system.
- the OLED array 510 emits light at the intersection of the parallel anodes in a first direction and the parallel cathodes in the perpendicular direction.
- the architecture of the OLED array 510 conveniently provides locations for the pixels of the image sensor array 224 to receive light scattered from the blood vessels 212 .
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Abstract
Description
- Payment card fraud costs financial institutions many billions of dollars a year and impacts tens of millions of consumers a year. Currently, payment cards use either a personal identification number (PIN) or a password for authentication purposes. However, PINs and passwords can be hacked and are widely regarded as the weakest link in security for these cards.
- The accompanying drawings illustrate various examples of the principles described below. The examples and drawings are illustrative rather than limiting.
-
FIG. 1A depicts an example portable card that includes a vascular pattern recognition system as described herein. -
FIG. 1B-1E depict examples of vascular pattern recognition systems. -
FIG. 2A depicts a top view of an example detection region on a portable card used with a vascular pattern recognition system. -
FIG. 2B depicts a side view of an example vascular pattern detection system. -
FIG. 3A depicts a top view of an example detection region on a portable card used with a vascular pattern recognition system. -
FIG. 3B depicts a side view of another example vascular pattern detection system. -
FIG. 4A depicts a side view of an example vascular pattern detection system. -
FIG. 4B depicts an isometric view of an example vascular pattern detection system. -
FIG. 5A depicts a side view of an example vascular pattern detection system. -
FIG. 5B depicts a top view of an example vascular pattern detection system. - Vascular pattern recognition is a highly secure biometric authentication method that uses the unique blood vessel patterns in a user's finger or palm as a means of identification. An image of the user's blood vessels may be pre-registered and stored for comparison at a later time to a real-time image of the living blood vessels of the user to identify the user. Because living blood vessels are used for user authentication, it would be extremely difficult to deceive a vascular pattern recognition system. While vascular pattern recognition systems have been used to authenticate a user's identity, known systems are expensive and bulky.
- Described below are vascular pattern recognition systems for portable secure cards, such as credit cards and smart badges, having a thickness of less than approximately two millimeters. The system uses flexible hybrid electronics and photonics technology to integrate a compact finger vascular pattern detection and authentication system on the card, resulting in a card that provides enhanced security protection compared to personal identification number (PIN) or signature security systems.
-
FIG. 1A depicts an exampleportable card 100 that includes a vascularpattern recognition system 120. Theportable card 100 may be a secure card used in conjunction with an authentication and authorization system, such as may be used with a credit card or smart badge. The vascularpattern recognition system 120 may communicate with a card reader (not shown) contactlessly via a near field communication (NFC)antenna 130 or using a contact method via asmart chip 140. Communications from the vascularpattern recognition system 120 to the card reader may include an authorization code upon confirmation of the identity of the user of theportable card 100 based on the user's finger vascular pattern. In some implementations, theportable card 100 is thin, having a thickness of approximately two millimeters or less. Further, the vascularpattern recognition system 120 integrated on theportable card 100 also has a thickness of approximately two millimeters or less. In some implementations, the vascular pattern recognition system may have an area on theportable card 100 that is approximately 25×30 mm2 or smaller. - As shown in the example of
FIG. 1B , a vascularpattern recognition system 120 may include a vascularpattern detection system 125, animage processor 162 and asecurity processor 164. The vascularpattern detection system 125 can obtain image data of blood vessels of a finger to be swiped across a detection area on the portable card. The vascularpattern detection system 125 may include a near infrared (NIR)light source 152 and animage sensor array 154. Thelight source 152 should emit in the NIR, within a wavelength range of approximately 800 nm to 1000 nm. At these wavelengths, the light is transmitted through human tissue, ie, the skin, but is absorbed and scattered by the blood in the blood vessels. In some implementations, thelight source 152 may be light-emitting diodes (LEDs), such as GaAs and organic LEDs, which can emit light in the NIR wavelength range. In some implementations, theimage sensor array 154 may be a complementary metal-oxide semiconductor (CMOS) image sensor array, and in other implementations, theimage sensor array 154 may be a printed thin-film transistor-based photodiode image sensor array. - The
image processor 162 processes the image data obtained by the vascularpattern detection system 125 to generate a scanned vascular pattern. For example, in some implementations, theimage sensor array 154 may have a length smaller than a length of a person's fingertip where the vascular pattern is located because a smallerimage sensor array 154 is more cost effective. Thus, the width of theimage sensor array 154 may be approximately an adult finger width across, approximately 2-3 cm, while the length of theimage sensor array 154 may be shorter than the width. In this situation, as a person swipes a finger across the detection area on the portable card, the obtained image data may include a series of images of the finger's vascular pattern, and theimage processor 162 may use an image stitching algorithm on the series of images to stitch together the scanned images to generate a scanned vascular pattern. A similar stitching algorithm is used for scanning finger fingerprints. Further, theimage processor 162 compares the scanned vascular pattern, which may be a stitched vascular pattern, to a pre-stored pattern stored in a memory location on the portable card to authenticate the image data. Scanned vascular pattern data may include relative locations of blood vessel branching points, blood vessel thickness, and blood vessel branching angles. The pre-stored pattern may be a pre-registered image data of a vascular pattern of an authorized user. - The
security processor 164 generates a transaction or authentication code to authorize a transaction upon authentication of the image data, where the transaction code is transmitted through a contact method with a card reader or contactlessly via NFC. - The vascular
pattern detection system 125, theimage processor 162, and thesecurity processor 164 may be implemented using a one-chip or a two-chip system. A one-chip system may be beneficial because the elements on the chip may be integrated together into a smaller area, providing a reduction in a lower cost design. A two-chip system may have a different benefit, where the financial institution that issues the card, such as a credit card issuer, may generate its own security chip with a security processor, and the non-secure portion, such as the vascularpattern detection system 125, may be manufactured by a different manufacturer.FIG. 1C-1E depict examples of vascularpattern recognition systems 120. -
FIG. 1C depicts an example of a two-chip system where the vascularpattern detection system 125 and theimage processor 162 are part of afirst chip 171 on the portable card, and thesecurity processor 164 is part of asecond chip 172 on the portable card. Thepre-stored pattern 166 may be stored on thefirst chip 171. Thefirst chip 171 and thesecond chip 172 are distinct and communicatively coupled. Theimage processor 162 processes the image data obtained by the vascularpattern detection system 125, and theimage processor 162 sends an indication of authentication of the image data to thesecurity processor 164. Thus, if the user's vascular pattern matches the pre-stored pattern, thesecurity processor 164 may generate a transaction code. -
FIG. 1D depicts an example of a two-chip system where the vascularpattern detection system 125 is part of afirst chip 173 on the portable card, and thesecurity processor 164 and theimage processor 162 are part of asecond chip 174 on the portable card. Thepre-stored pattern 166 may be stored on thesecond chip 174. Thefirst chip 173 and thesecond chip 174 are distinct and communicatively coupled. The image data obtained by the vascularpattern detection system 125 is transmitted to theimage processor 162 for processing, and theimage processor 162 sends an indication of authentication of the image data to thesecurity processor 164. -
FIG. 1E depicts an example of a one-chip system where the vascularpattern detection system 125, theimage processor 162, and thesecurity processor 164 are part of asingle chip 175 on the portable card, and thepre-stored pattern 166 is stored on thesingle chip 175. Theimage processor 162 processes the image data obtained by the vascularpattern detection system 125, and theimage processor 162 sends an indication of authentication of the image data to thesecurity processor 164. -
FIGS. 2A and 3A each show a top view of examples ofdetection regions detection region finger 210 is to be swiped across a length of thedetection region blood vessels 212 may be detected and authenticated by the vascular pattern recognition system. In the example ofFIG. 2A , thedetection region 220 is round, having a diameter approximately a finger's width across. The recessed region may have a firstsloping edge 221 along the width on a first side and a secondsloping edge 223 along the width on a second side opposite the first side. In the example ofFIG. 3A , thedetection region 320 is square, where the length of each side is approximately a finger's width across. However, thedetection region -
FIGS. 2B and 3B each show a side view of a vascular pattern detection system based on lateral placement of a NIR light source and an image sensor array.FIG. 2B depicts a side view of an example vascular pattern detection system that includes a firstNIR LED array 222 positioned along the firstsloping edge 221 and animage sensor array 224 to receive light emitted by the first NIR LED array (representativesolid line ray 222 a) and scattered (representative dotted line rays 222 b) from blood vessels of a finger to be swiped along the length of the recessedregion 220. In some implementations, theimage sensor array 224 is positioned on the secondsloping edge 223 of the recessed region, as shown in the example ofFIG. 2B . - In some implementations, the
image sensor array 224 may be positioned, as shown in the example ofFIG. 3B , where an example vascular pattern detection system includes a recessedregion 320. A firstNIR LED array 330 is positioned along the first sloping edge 331 of the recessedregion 320, and animage sensor array 224 is positioned at a bottom 333 of the recessedregion 320 to receive light emitted by the first NIR LED array (representative ray 330 a) and scattered (representative rays 330 b) from blood vessels of a finger to be swiped along the length of the recessedregion 320. Further, a secondNIR LED array 334 may be positioned along a secondsloping edge 332 of the recessedregion 320, where theimage sensor array 224 further receives light emitted by thesecond NIR LED 334 array and scattered from the blood vessels of thefinger 210. As shown in the example ofFIG. 3A , the recessedregion 320 may have other NIR LED arrays around the perimeter to illuminate thefinger 320 to be swiped across therecess region 320. - Additionally, for either configuration in the examples of
FIGS. 2B and 3B , a NIR filter andspacer 226 may be positioned over theimage sensor array 224, and amicrolens array 228 may be positioned over the NIR filter andspacer 226. The NIR filter andspacer 226 blocks wavelengths of light that are not within the range of wavelengths emitted by theNIR LED arrays image sensor array 224 is sensitive to other wavelengths of light, such as ambient light, that may interfere with the desired image data of the vascular pattern to be detected. Additionally, the NIR filter andspacer 226 provides a pre-defined focusing distance between the microlenses in themicrolens array 228 and the pixels of theimage sensor array 224, as shown by therepresentative rays 351, 352 in the example ofFIG. 3B . -
FIGS. 4A and 5A each depict a side view of an example vascular pattern detection system based on vertical placement of a NIR light source and an image sensor array.FIG. 4A depicts a side view of an example vascular pattern detection system that includes a scanning area having a width approximately a finger's width across and alength 401 that may be shorter than the width. The vascular pattern detection system also includes animage sensor array 224 within the scanning area. As described above, a NIR filter andspacer 226 is positioned over theimage sensor array 224, and amicrolens array 228 is positioned over the NIR filter andspacer 226. There is also a NIR light source to emit light above themicrolens array 228 toward afinger 210 to be swiped along the length of the scanning area, where theimage sensor array 224 receives light emitted by the NIR light source and scattered fromblood vessels 212 of thefinger 210. - In some implementations, as shown in the example of
FIG. 4A , the NIR light source includes anedge emitting LED 410 and alight guide 420 positioned over a portion of themicrolens array 228, where light emitted by the edge emitting LED 410 (representative rays 412) couples into thelight guide 420 and travels along thelight guide 420 via total internal reflection. There may be more than oneedge emitting LED 410 that emits light that couples into thelight guide 420. Further, there may be multiplelight guides 420, such as shown in the example ofFIG. 4B , an isometric view of the example vascular pattern detection system. - Returning to
FIG. 4A ,light scatterers 440 are positioned outside thelight guide 420 on a first surface closest to themicrolens array 228 to scatter light (representative ray 413) in thelight guide 420 toward thefinger 210, where thelight scatterers 440 are positioned around afirst pinhole array 461 on a surface of thelight guide 420 closer to theimage sensor array 224 than thefinger 210. Asecond pinhole array 462 may be positioned on an opposite surface of thelight guide 420, closer to where thefinger 210 may be swiped across the scanning area. Thesecond pinhole array 462 is aligned with thefirst pinhole array 461, such that the alignedpinhole arrays image sensor array 224, as shown in the isometric view ofFIG. 4B . Further,pinhole arrays light guides 420 to allow light from the various light guides 420 to be directed to the pixels of theimage sensor array 224. Additionally, because thepinhole arrays image sensor array 224 and used to generate a three-dimensional image of the blood vessels of the finger, not merely a two-dimensional image. - In some implementations, a diffuser layer 430 is positioned between the emitted light 412 from the NIR light source and the
finger 210 to be scanned. The diffuser layer 430 collimates light from the light scatterers 440 (representative rays 414), and the diffuser layer 430 is positioned around thesecond pinhole array 462. - In some implementations, a
reflection film 450 may be adhered to a surface of thelight scatterers 440 away from thelight guide 420. Thereflection film 450 is a polarized reflecting plane that transmits light from the vertical direction while reflecting light from other directions. As a result, light is scattered in all directions from thelight scatterers 440 toward the finger, while light traveling vertically downward 224 from theblood vessel 212 is permitted to pass through to theimage sensor array 224. -
FIG. 5A depicts a side view of an example vascular pattern detection system. Similar toFIG. 4A , the vascular pattern detection system includes a scanning area having a width approximately a finger's width across and alength 501 that may be shorter than the width. As with the other example vascular detect systems, the vascular pattern detection system also includes animage sensor array 224 within the scanning area, a NIR filter andspacer 226 positioned over theimage sensor array 224, and amicrolens array 228 positioned over the NIR filter andspacer 226. The NIR light source that emits light above themicrolens array 228 toward afinger 210 to be swiped along the length of the scanning area may be an organic light-emitting diode (OLED)array 510 positioned above themicrolens array 228. TheOLED array 510 emits light (representative solid line rays 512) directly upward toward thefinger 210 to be swiped across the scanning area, and the light is scattered (representative dotted line rays) fromblood vessels 212 of thefinger 210 to theimage sensor array 224. -
FIG. 5B depicts a top view of the example vascular pattern detection system. TheOLED array 510 emits light at the intersection of the parallel anodes in a first direction and the parallel cathodes in the perpendicular direction. The architecture of theOLED array 510 conveniently provides locations for the pixels of theimage sensor array 224 to receive light scattered from theblood vessels 212. - As used in the specification and claims herein, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
Claims (15)
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11659391B2 (en) | 2019-07-24 | 2023-05-23 | Bank Of America Corporation | Real-time authentication using a mobile device on a high generation cellular network |
US12213764B2 (en) | 2021-03-05 | 2025-02-04 | Samsung Electronics Co., Ltd. | Bio imaging system and bio imaging method |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR102223279B1 (en) * | 2014-07-08 | 2021-03-05 | 엘지전자 주식회사 | Apparatus for measuring condition of object and wearable device |
US11080505B2 (en) * | 2018-04-10 | 2021-08-03 | Waleed Sami Haddad | Under-screen fingerprint reader |
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US11380125B2 (en) * | 2019-06-21 | 2022-07-05 | Waleed Sami Haddad | Under-screen fingerprint reader |
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CN112014990A (en) * | 2020-09-01 | 2020-12-01 | 武汉华星光电技术有限公司 | Liquid crystal display panel and liquid crystal display device |
Citations (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20404A (en) * | 1858-06-01 | Mantel-bar | ||
US4582985A (en) * | 1981-03-18 | 1986-04-15 | Loefberg Bo | Data carrier |
US20030016345A1 (en) * | 2001-07-19 | 2003-01-23 | Akio Nagasaka | Finger identification apparatus |
US20030103686A1 (en) * | 2001-12-04 | 2003-06-05 | Canon Kabushiki Kaisha | Image input device |
US6576490B2 (en) * | 2001-05-09 | 2003-06-10 | National Research Council Of Canada | Method for micro-fabricating a pixelless infrared imaging device |
US20050240778A1 (en) * | 2004-04-26 | 2005-10-27 | E-Smart Technologies, Inc., A Nevada Corporation | Smart card for passport, electronic passport, and method, system, and apparatus for authenticating person holding smart card or electronic passport |
US20070003112A1 (en) * | 2005-06-30 | 2007-01-04 | Fujitsu Limited | Biometrics authentication method biometrics authentication device and blood vessel image reading device |
US7245745B2 (en) * | 2003-03-04 | 2007-07-17 | Hitachi, Ltd. | Personal authentication device |
US20090161920A1 (en) * | 2007-12-25 | 2009-06-25 | Hitachi Maxell, Ltd. | Biometric information acquisition apparatus, image acquisition apparatus, and electronic equipment |
US7623689B2 (en) * | 2003-11-18 | 2009-11-24 | Canon Kabushiki Kaisha | Image pick-up apparatus including luminance control of irradiation devices arranged in a main scan direction |
US20100046807A1 (en) * | 2008-08-25 | 2010-02-25 | Hideo Sato | Vein Imaging Apparatus, Vein Imaging Method and Vein Authentication Apparatus |
US20100080422A1 (en) * | 2008-09-30 | 2010-04-01 | Hideo Sato | Finger Vein Authentication Apparatus and Finger Vein Authentication Method |
US20100230435A1 (en) * | 2009-03-13 | 2010-09-16 | Wegelin Jackson W | Touch-Free Biometric-Enabled Dispenser |
US20100231125A1 (en) * | 2009-03-12 | 2010-09-16 | Sheng Li | Organic light emitting device to emit in near infrared |
US7873408B2 (en) * | 2004-12-28 | 2011-01-18 | Sony Corporation | Bioimaging apparatus |
US20110174874A1 (en) * | 2010-01-19 | 2011-07-21 | Poznansky Amir | Transaction Card With Improved Security Features |
US8204284B2 (en) * | 2009-02-19 | 2012-06-19 | Gingy Technology Inc. | Fingerprint identifying system using a set of microstructure layers formed on one of top and bottom faces of light-transmissive finger press plate |
Family Cites Families (29)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5177802A (en) * | 1990-03-07 | 1993-01-05 | Sharp Kabushiki Kaisha | Fingerprint input apparatus |
FR2754369B1 (en) * | 1996-10-04 | 1998-12-18 | Thomson Csf | RELIEF FINGERPRINT ACQUISITION SYSTEM AND ACQUISITION METHOD |
AU6511699A (en) * | 1998-10-12 | 2000-05-01 | Veridicom, Inc. | A protective enclosure for sensor devices |
US7543156B2 (en) | 2002-06-25 | 2009-06-02 | Resilent, Llc | Transaction authentication card |
US7146029B2 (en) * | 2003-02-28 | 2006-12-05 | Fujitsu Limited | Chip carrier for fingerprint sensor |
US7274808B2 (en) * | 2003-04-18 | 2007-09-25 | Avago Technologies Ecbu Ip (Singapore)Pte Ltd | Imaging system and apparatus for combining finger recognition and finger navigation |
US8175345B2 (en) * | 2004-04-16 | 2012-05-08 | Validity Sensors, Inc. | Unitized ergonomic two-dimensional fingerprint motion tracking device and method |
US8229184B2 (en) * | 2004-04-16 | 2012-07-24 | Validity Sensors, Inc. | Method and algorithm for accurate finger motion tracking |
US7318550B2 (en) | 2004-07-01 | 2008-01-15 | American Express Travel Related Services Company, Inc. | Biometric safeguard method for use with a smartcard |
US20060093192A1 (en) * | 2004-11-03 | 2006-05-04 | Bechtel J S | Finger guide device |
US20070057929A1 (en) * | 2005-09-13 | 2007-03-15 | Tong Xie | Navigation device with a contoured region that provides tactile feedback |
US7557338B2 (en) * | 2006-03-14 | 2009-07-07 | Avago Technologies General Ip (Singapore) Pte. Ltd. | Electronic device with integrated optical navigation module and microlens array therefore |
GB2437557B (en) | 2006-03-29 | 2008-08-20 | Motorola Inc | Electronic smart card and a method of use of the smart card |
JP4182988B2 (en) * | 2006-04-28 | 2008-11-19 | 日本電気株式会社 | Image reading apparatus and image reading method |
US8180119B2 (en) * | 2006-12-04 | 2012-05-15 | Sony Corporation | Imaging apparatus and imaging method |
US8180122B2 (en) * | 2007-02-08 | 2012-05-15 | Disney Enterprise, Inc. | Ergonomic finger guide for biometric finger scanner |
JP2008210105A (en) * | 2007-02-26 | 2008-09-11 | Hitachi Maxell Ltd | Living body information acquisition device |
FR2913788B1 (en) * | 2007-03-14 | 2009-07-03 | Sagem Defense Securite | METHOD AND APPARATUS FOR IDENTIFYING AN INDIVIDUAL BY OPTICAL CAPTURE OF AN IMAGE OF A BODY FOOTPRINT |
JP4604074B2 (en) * | 2007-10-09 | 2010-12-22 | 日立オートモティブシステムズ株式会社 | Finger vein authentication apparatus and method |
US8276816B2 (en) * | 2007-12-14 | 2012-10-02 | Validity Sensors, Inc. | Smart card system with ergonomic fingerprint sensor and method of using |
JP2010094499A (en) * | 2008-09-16 | 2010-04-30 | Hitachi Maxell Ltd | Image acquisition apparatus and biometric information acquisition apparatus |
DE102009005092A1 (en) * | 2009-01-19 | 2010-09-02 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Device for optical navigation and its use |
JP5056798B2 (en) * | 2009-06-08 | 2012-10-24 | 日本電気株式会社 | Determination device, fingerprint input device, determination method, and determination program |
KR101111381B1 (en) | 2009-11-17 | 2012-02-24 | 최운호 | User identification system, apparatus, smart card and method for ubiquitous identity management |
CN103443822B (en) * | 2011-03-25 | 2017-11-24 | 日本电气株式会社 | Verify equipment and verification method |
US20140084059A1 (en) | 2011-05-11 | 2014-03-27 | Joseph Sierchio | Universal interactive smart card device |
WO2013146760A1 (en) * | 2012-03-27 | 2013-10-03 | 日本電気株式会社 | Authentication device, prism body for use in authentication, and authentication method |
US20130336546A1 (en) * | 2012-06-15 | 2013-12-19 | Aoptix Technologies, Inc. | Biometric enclosure for a mobile device |
JP2015185947A (en) * | 2014-03-20 | 2015-10-22 | 株式会社東芝 | imaging system |
-
2016
- 2016-06-10 US US15/179,156 patent/US10074005B2/en active Active
-
2018
- 2018-08-22 US US16/109,716 patent/US20190005301A1/en not_active Abandoned
Patent Citations (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20404A (en) * | 1858-06-01 | Mantel-bar | ||
US4582985A (en) * | 1981-03-18 | 1986-04-15 | Loefberg Bo | Data carrier |
US6576490B2 (en) * | 2001-05-09 | 2003-06-10 | National Research Council Of Canada | Method for micro-fabricating a pixelless infrared imaging device |
US20030016345A1 (en) * | 2001-07-19 | 2003-01-23 | Akio Nagasaka | Finger identification apparatus |
US20030103686A1 (en) * | 2001-12-04 | 2003-06-05 | Canon Kabushiki Kaisha | Image input device |
US7245745B2 (en) * | 2003-03-04 | 2007-07-17 | Hitachi, Ltd. | Personal authentication device |
US7623689B2 (en) * | 2003-11-18 | 2009-11-24 | Canon Kabushiki Kaisha | Image pick-up apparatus including luminance control of irradiation devices arranged in a main scan direction |
US20050240778A1 (en) * | 2004-04-26 | 2005-10-27 | E-Smart Technologies, Inc., A Nevada Corporation | Smart card for passport, electronic passport, and method, system, and apparatus for authenticating person holding smart card or electronic passport |
US7873408B2 (en) * | 2004-12-28 | 2011-01-18 | Sony Corporation | Bioimaging apparatus |
US20070003112A1 (en) * | 2005-06-30 | 2007-01-04 | Fujitsu Limited | Biometrics authentication method biometrics authentication device and blood vessel image reading device |
US20090161920A1 (en) * | 2007-12-25 | 2009-06-25 | Hitachi Maxell, Ltd. | Biometric information acquisition apparatus, image acquisition apparatus, and electronic equipment |
US20100046807A1 (en) * | 2008-08-25 | 2010-02-25 | Hideo Sato | Vein Imaging Apparatus, Vein Imaging Method and Vein Authentication Apparatus |
US20100080422A1 (en) * | 2008-09-30 | 2010-04-01 | Hideo Sato | Finger Vein Authentication Apparatus and Finger Vein Authentication Method |
US8204284B2 (en) * | 2009-02-19 | 2012-06-19 | Gingy Technology Inc. | Fingerprint identifying system using a set of microstructure layers formed on one of top and bottom faces of light-transmissive finger press plate |
US20100231125A1 (en) * | 2009-03-12 | 2010-09-16 | Sheng Li | Organic light emitting device to emit in near infrared |
US20100230435A1 (en) * | 2009-03-13 | 2010-09-16 | Wegelin Jackson W | Touch-Free Biometric-Enabled Dispenser |
US20110174874A1 (en) * | 2010-01-19 | 2011-07-21 | Poznansky Amir | Transaction Card With Improved Security Features |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11659391B2 (en) | 2019-07-24 | 2023-05-23 | Bank Of America Corporation | Real-time authentication using a mobile device on a high generation cellular network |
US12213764B2 (en) | 2021-03-05 | 2025-02-04 | Samsung Electronics Co., Ltd. | Bio imaging system and bio imaging method |
Also Published As
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US20170357843A1 (en) | 2017-12-14 |
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