CN113609953A - Non-contact palm vein area identification method, system and storage medium - Google Patents
Non-contact palm vein area identification method, system and storage medium Download PDFInfo
- Publication number
- CN113609953A CN113609953A CN202110875873.7A CN202110875873A CN113609953A CN 113609953 A CN113609953 A CN 113609953A CN 202110875873 A CN202110875873 A CN 202110875873A CN 113609953 A CN113609953 A CN 113609953A
- Authority
- CN
- China
- Prior art keywords
- vein
- palm
- image
- region
- frame
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 210000003462 vein Anatomy 0.000 title claims abstract description 112
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000003708 edge detection Methods 0.000 claims abstract description 15
- 238000007781 pre-processing Methods 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 5
- 238000009432 framing Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000003542 behavioural effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001815 facial effect Effects 0.000 description 1
- 230000005021 gait Effects 0.000 description 1
- 229920002050 silicone resin Polymers 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Quality & Reliability (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Collating Specific Patterns (AREA)
Abstract
The invention relates to the technical field of biological identification, and provides a non-contact palm vein region identification method, a non-contact palm vein region identification system and a non-contact palm vein region identification storage medium, wherein when palm vein identification is carried out, image preprocessing is carried out on an obtained vein code scanning image to improve the accuracy of later image identification; the method has the advantages that the edge detection is carried out by determining the preset central point according to the front-end acquisition equipment, the region of interest in the vein scanning image is determined, and the region of interest can be dynamically extracted according to the actually acquired image, so that the accuracy of dividing the palm vein image from the vein scanning image is improved, the palm shape identification freedom of a user is improved, the palm vein identification efficiency is improved by rapidly extracting the palm vein image, and the good use experience is provided for the user.
Description
Technical Field
The invention relates to the technical field of biological identification, in particular to a non-contact palm vein region identification method, a non-contact palm vein region identification system and a storage medium.
Background
Biometric identification is a technique for identifying an individual by using physiological characteristics (fingerprint, iris, facial phase, DNA, etc.) or behavioral characteristics (gait, keystroke habit, etc.) inherent to a human body by a computer. In these biometric identification techniques, fingerprint identification has the characteristics of strong uniqueness, stability, usability and the like, and thus, the application is extremely wide. However, in fingerprint recognition, it is required that a user keeps a finger clean and smooth when entering the fingerprint, and any dirt or stain existing on the fingerprint causes difficulty in recognition, and the fingerprint is easy to be forged, and even a cloned fingerprint made of silicone resin appears, resulting in a low safety factor of the fingerprint recognition technology. Therefore, the unique and difficult-to-forge vein identification enters the visual field of people, but the collection difficulty of the palm vein features is increased greatly due to the fact that the palm veins can obtain more feature information.
The most difficult point of the development of the palm vein identification technology and the primary key point of identification and authentication are palm positioning. The technical principle of the palm vein recognition technology in the market at present is as follows: the camera is used for identifying points between fingers to connect lines, and then a square area confirmed by 90 degrees is drawn to the other side, so that the following defects exist:
(1) in actual experience, the palm size of each person is different, and the palm posture is also strange during vein recognition, so that the positioning concave points between the fingers of the palm are difficult to effectively recognize, the recognition efficiency of the palm veins is too low, and the user experience feeling is poor.
(2) Because the identification limitation of the palm veins is large (the palm veins need to be aligned with the placement position and the placement direction), the user degree of freedom is low, the difficulty and the time for people to learn and use the product are increased, and the experience of a product user is seriously influenced.
Disclosure of Invention
The invention provides a non-contact palm vein region identification method, a non-contact palm vein region identification system and a storage medium, and solves the technical problems of low degree of freedom and poor identification efficiency of the conventional palm vein identification technology.
In order to solve the technical problems, the invention provides a non-contact palm vein area identification method, which comprises the following steps:
s1, acquiring a vein scanning image acquired by front-end acquisition equipment, and performing image preprocessing;
s2, determining a preset central point according to the front-end acquisition equipment;
s3, performing edge detection according to the preset central point, and determining an interested area in the vein scanning image;
and S4, dividing a palm vein image from the vein scanning image according to the region of interest.
When the palm vein recognition is carried out, the image preprocessing is carried out on the obtained vein code scanning image to improve the accuracy of the later image recognition; the method has the advantages that the edge detection is carried out by determining the preset central point according to the front-end acquisition equipment, the region of interest in the vein scanning image is determined, and the region of interest can be dynamically extracted according to the actually acquired image, so that the accuracy of dividing the palm vein image from the vein scanning image is improved, the palm shape identification freedom of a user is improved, the palm vein identification efficiency is improved by rapidly extracting the palm vein image, and the good use experience is provided for the user.
In further embodiments, the step S1 includes:
s11, acquiring a vein scanning image acquired by front-end acquisition equipment;
and S12, Otsu filtering processing is carried out on the vein scanning image, and a palm outline is obtained.
According to the scheme, before the region of interest is extracted, Otsu filtering processing is carried out on the vein scanning image, the foreground and the background can be segmented, the palm outline is highlighted, and interference of irrelevant factors in the background on palm vein recognition is avoided.
The step S2 specifically includes: and acquiring the image coordinate of a camera in the front-end acquisition equipment, and defining the image coordinate as a preset central point.
According to the scheme, the image coordinate of the camera in the front-end acquisition equipment is defined as the preset central point, and the palm vein recognition habit of a user is considered, so that the palm vein area with the largest range and the most appropriate area can be obtained as far as possible, and the accuracy of palm vein recognition is improved.
In further embodiments, the step S3 includes:
s31, establishing a circular selection frame by taking the preset central point as a starting point and an initial radius;
s32, performing region framing on the vein scanning image according to the circular frame;
s33, performing edge detection on the frame selection area, judging whether the circular selection frame is selected to the palm-shaped outline from the vein scanning image middle frame, if so, defining the region of interest by the current circular selection frame, and if not, expanding the circular selection frame according to the preset step until the palm-shaped outline is selected.
In a further embodiment, in step S33, the edge detection is performed on the frame-selected area, and it is determined whether the circular frame is framed from the vein scan image to a palm-type outline, specifically: and carrying out edge detection and image recognition on image lines of an edge area of a frame selection area, judging whether the frame selection edge of the circular selection frame is overlapped with any boundary in the palm-shaped outline or not, and if so, judging that the circular selection frame is framed from the vein scanning image to the palm-shaped outline.
According to the scheme, a circular selection frame is established by taking a preset central point as a starting point and an initial radius, a circle is drawn from inside to outside by a preset step, whether a frame selection edge of the circular selection frame is overlapped with any boundary in a palm-shaped outline or not is taken as a mark, an interested region is determined in a vein scanning image, the palm-shaped region in the optimal range can be screened out for palm vein recognition, the image quality of the interested region is high, the data size is large, and subsequent feature extraction and comparison of the palm vein recognition are facilitated.
In further embodiments, in said step S1: the front end acquisition equipment comprises a fixed panel, a camera arranged at the center of the fixed panel and a plurality of near infrared spot lights arranged around the camera as the center.
The present invention also provides a storage medium having stored thereon a computer program for implementing a non-contact palm vein region identification method as described above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
The invention also provides a non-contact palm vein recognition system, which comprises electrically connected front-end acquisition equipment and a central control module, wherein the central control module is in data connection with a background database;
the front-end acquisition equipment is used for acquiring a vein scanning image of a user; the front-end acquisition equipment comprises a fixed panel, a camera arranged at the center of the fixed panel and a plurality of near-infrared spot lights arranged around the camera;
the central control module comprises one of the storage media;
the background database stores palm vein feature data and corresponding identity information.
Drawings
Fig. 1 is a flowchart of a non-contact palm vein region identification method according to embodiment 1 of the present invention;
fig. 2 is a schematic structural diagram of a front-end acquisition device provided in embodiment 1 or 3 of the present invention;
FIG. 3 is a schematic diagram of the region of interest delineation provided in embodiment 1 of the present invention;
fig. 4 is a system framework diagram of a non-contact palm vein region identification system according to embodiment 1 of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, which are given solely for the purpose of illustration and are not to be construed as limitations of the invention, including the drawings which are incorporated herein by reference and for illustration only and are not to be construed as limitations of the invention, since many variations thereof are possible without departing from the spirit and scope of the invention.
Example 1
As shown in fig. 1, 2, and 3, the non-contact palm vein region identification method according to the embodiment of the present invention includes:
s1, acquiring the vein scanning image acquired by the front-end acquisition equipment, and performing image preprocessing, wherein the image preprocessing comprises the following steps of S11-S12:
s11, acquiring a vein scanning image acquired by front-end acquisition equipment;
in this embodiment, the front-end collecting device includes a fixed panel, a camera installed at the center of the fixed panel, and a plurality of near-infrared spot lights installed around the camera.
When the palm vein is identified, the palm can point to any direction and is aligned to the camera, namely the center of the cross connecting line intersection in the picture 2, and the palm is suspended, so that the available vein scanning image can be obtained.
And S12, Otsu filtering processing is carried out on the vein scanning image, and the palm outline is obtained.
In the embodiment, before the ROI extraction is performed on the vein scan image, Otsu filtering processing is performed, so that the foreground and the background can be segmented, the palm contour is highlighted, and the interference of irrelevant factors in the background on the palm vein identification is avoided.
S2, determining a preset central point according to the front-end acquisition equipment, specifically: acquiring the image coordinate of a camera in front-end acquisition equipment, and defining the image coordinate as a preset central point.
In the embodiment, the image coordinates of the camera in the front-end acquisition device are defined as the preset central point, and the palm vein recognition habit of the user is considered, so that the palm vein area with the largest range and the most appropriate area can be obtained as far as possible, and the accuracy of palm vein recognition is improved.
S3, performing edge detection according to a preset central point, and determining a region of interest ROI in the vein scanning image, including steps S31-S33:
s31, establishing a circular selection frame by taking the preset central point as a starting point and the initial radius;
s32, performing region framing on the vein scanning image according to the circular selection frame;
s33, edge detection is carried out on the frame selection area, whether the circular selection frame is selected from the vein scanning image to the palm-shaped outline or not is judged, if yes, the ROI is defined by the current circular selection frame, and if not, the circular selection frame is expanded according to the preset steps until the palm-shaped outline is selected by the frame.
Wherein, carry out edge detection to the frame selection region, judge whether circular selection frame is from the vein scanning image middle frame selection to palm type profile, specifically do: and carrying out edge detection and image recognition on the image lines of the edge area of the frame selection area, judging whether the frame selection edge of the circular selection frame is overlapped with any boundary in the palm-shaped profile, and if so, judging that the circular selection frame is framed from the vein scanning image to the palm-shaped profile.
In this embodiment, the preset step may be set according to the precision of the processor and the user's requirement.
According to the scheme, a circular selection frame is established by taking a preset central point as a starting point and an initial radius, a circle is drawn from inside to outside by a preset step, whether a frame selection edge of the circular selection frame is overlapped with any boundary in a palm-shaped outline or not is taken as a mark, a region of interest (ROI) is determined in a vein scanning image, the palm-shaped area in an optimal range can be screened out for palm vein identification, the image quality of the ROI in the region of interest is high, the data size is large, and subsequent feature extraction and comparison of the palm vein identification are facilitated.
S4, a palm vein image is segmented from the vein scan image according to the region of interest ROI.
When the palm vein recognition is carried out, the image preprocessing is carried out on the obtained vein code scanning image to improve the accuracy of the later image recognition; the method comprises the steps of determining a preset central point according to front-end acquisition equipment for edge detection, determining a region of interest (ROI) in a vein scanning image, and dynamically extracting the ROI according to an actually acquired image, so that the accuracy of dividing a palm vein image from the vein scanning image is improved, the palm shape identification freedom of a user is improved, the palm vein identification efficiency is improved by rapidly extracting the palm vein image, and good use experience is provided for the user.
Example 2
An embodiment of the present invention further provides a storage medium, on which a computer program is stored, where the computer program is used to implement the non-contact palm vein region identification method provided in embodiment 1 above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
Example 3
The reference numerals appearing in the drawings of the present embodiment include: the system comprises a front-end acquisition device 1, a fixed panel 11, a camera 12 and a near infrared spot lamp 13; a central control module 2 and a background database 3.
The embodiment of the invention also provides a non-contact palm vein recognition system, which is shown in fig. 2 and 4 and comprises a front-end acquisition device 1 and a central control module 2, wherein the central control module 2 is in data connection with a background database 3;
the front-end acquisition equipment 1 is used for acquiring a vein scanning image of a user;
in the present embodiment, the front end collecting apparatus 1 includes a fixed panel 11, a camera 12 installed at a central position of the fixed panel 11, and a plurality of near infrared light lamps 13 installed around the camera 12;
the central control module 2 is used for executing steps S1 to S4 in embodiment 1, and palm vein feature identification and palm vein feature comparison to realize palm vein identification by using a storage medium including one of the above-mentioned embodiments 2.
The background database 3 stores palm vein feature data and corresponding identity information.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (8)
1. A non-contact palm vein region identification method is characterized by comprising the following steps:
s1, acquiring a vein scanning image acquired by front-end acquisition equipment, and performing image preprocessing;
s2, determining a preset central point according to the front-end acquisition equipment;
s3, performing edge detection according to the preset central point, and determining an interested area in the vein scanning image;
and S4, dividing a palm vein image from the vein scanning image according to the region of interest.
2. The method for identifying a palm vein region in a non-contact manner as claimed in claim 1, wherein the step S1 comprises:
s11, acquiring a vein scanning image acquired by front-end acquisition equipment;
and S12, Otsu filtering processing is carried out on the vein scanning image, and a palm outline is obtained.
3. The method for identifying a palm vein region in a non-contact manner as claimed in claim 1, wherein the step S2 is specifically as follows: and acquiring the image coordinate of a camera in the front-end acquisition equipment, and defining the image coordinate as a preset central point.
4. The method for identifying a palm vein region in a non-contact manner as claimed in claim 1, wherein the step S3 comprises:
s31, establishing a circular selection frame by taking the preset central point as a starting point and an initial radius;
s32, performing region framing on the vein scanning image according to the circular frame;
s33, performing edge detection on the frame selection area, judging whether the circular selection frame is selected to the palm-shaped outline from the vein scanning image middle frame, if so, defining the region of interest by the current circular selection frame, and if not, expanding the circular selection frame according to the preset step until the palm-shaped outline is selected.
5. The method as claimed in claim 4, wherein in step S33, the edge detection is performed on the frame-selected area to determine whether the circular frame is framed from the vein scan image to a palm-shaped outline, specifically: and carrying out edge detection and image recognition on image lines of an edge area of a frame selection area, judging whether the frame selection edge of the circular selection frame is overlapped with any boundary in the palm-shaped outline or not, and if so, judging that the circular selection frame is framed from the vein scanning image to the palm-shaped outline.
6. The non-contact palm vein region identification method according to claim 1, wherein in the step S1: the front end acquisition equipment comprises a fixed panel, a camera arranged at the center of the fixed panel and a plurality of near infrared spot lights arranged around the camera as the center.
7. A storage medium having a computer program stored thereon, characterized in that: the computer program is for implementing a non-contact palm vein region identification method as claimed in claims 1-6.
8. A non-contact palm vein recognition system, characterized in that; the system comprises a front-end acquisition device and a central control module which are electrically connected, wherein the central control module is in data connection with a background database;
the front-end acquisition equipment is used for acquiring a vein scanning image of a user; the front-end acquisition equipment comprises a fixed panel, a camera arranged at the center of the fixed panel and a plurality of near-infrared spot lights arranged around the camera;
said central control module comprising a storage medium of said claim 7;
the background database stores palm vein feature data and corresponding identity information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110875873.7A CN113609953A (en) | 2021-07-30 | 2021-07-30 | Non-contact palm vein area identification method, system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110875873.7A CN113609953A (en) | 2021-07-30 | 2021-07-30 | Non-contact palm vein area identification method, system and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113609953A true CN113609953A (en) | 2021-11-05 |
Family
ID=78306339
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110875873.7A Pending CN113609953A (en) | 2021-07-30 | 2021-07-30 | Non-contact palm vein area identification method, system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113609953A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114612941A (en) * | 2022-05-11 | 2022-06-10 | 四川圣点世纪科技有限公司 | Palm vein feature-based multi-mode identity authentication method, device and system |
| WO2024016786A1 (en) * | 2022-07-18 | 2024-01-25 | 腾讯科技（深圳）有限公司 | Palm image recognition method and apparatus, and device, storage medium and program product |
| CN118097730A (en) * | 2024-04-28 | 2024-05-28 | 成都贝迪特信息技术有限公司 | ROI image extraction method for palm vein recognition |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111639562A (en) * | 2020-05-15 | 2020-09-08 | 圣点世纪科技股份有限公司 | Intelligent positioning method for palm region of interest |
| CN111932552A (en) * | 2020-07-21 | 2020-11-13 | 深圳睿心智能医疗科技有限公司 | Aorta modeling method and device |
| CN112053397A (en) * | 2020-07-14 | 2020-12-08 | 北京迈格威科技有限公司 | Image processing method, image processing device, electronic equipment and storage medium |
| CN112712521A (en) * | 2021-01-18 | 2021-04-27 | 佛山科学技术学院 | Automatic fundus optic disk positioning method based on global gradient search |
-
2021
- 2021-07-30 CN CN202110875873.7A patent/CN113609953A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111639562A (en) * | 2020-05-15 | 2020-09-08 | 圣点世纪科技股份有限公司 | Intelligent positioning method for palm region of interest |
| CN112053397A (en) * | 2020-07-14 | 2020-12-08 | 北京迈格威科技有限公司 | Image processing method, image processing device, electronic equipment and storage medium |
| CN111932552A (en) * | 2020-07-21 | 2020-11-13 | 深圳睿心智能医疗科技有限公司 | Aorta modeling method and device |
| CN112712521A (en) * | 2021-01-18 | 2021-04-27 | 佛山科学技术学院 | Automatic fundus optic disk positioning method based on global gradient search |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114612941A (en) * | 2022-05-11 | 2022-06-10 | 四川圣点世纪科技有限公司 | Palm vein feature-based multi-mode identity authentication method, device and system |
| WO2024016786A1 (en) * | 2022-07-18 | 2024-01-25 | 腾讯科技（深圳）有限公司 | Palm image recognition method and apparatus, and device, storage medium and program product |
| CN118097730A (en) * | 2024-04-28 | 2024-05-28 | 成都贝迪特信息技术有限公司 | ROI image extraction method for palm vein recognition |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR100826876B1 (en) | Iris recognition method and apparatus for thereof | |
| CN113609953A (en) | Non-contact palm vein area identification method, system and storage medium | |
| JP4305431B2 (en) | Image processing apparatus, mask creation method and program | |
| Hambalık | Fingerprint recognition system using artificial neural network as feature extractor: design and performance evaluation | |
| KR20050025927A (en) | The pupil detection method and shape descriptor extraction method for a iris recognition, iris feature extraction apparatus and method, and iris recognition system and method using its | |
| CN109376604B (en) | Age identification method and device based on human body posture | |
| JP2008529164A (en) | Iris recognition system and method | |
| JP2005222419A (en) | Biometrics information collation system | |
| He et al. | A new segmentation approach for iris recognition based on hand-held capture device | |
| CN111344703A (en) | User authentication device and method based on iris recognition | |
| JP2019502198A (en) | Finger joint and finger vein based biometric authentication method and apparatus | |
| CN109583279A (en) | A kind of fingerprint and refer to that vein combines recognizer | |
| JP2017211938A (en) | Biological information processor, biological information processing method and biological information processing program | |
| Aleem et al. | Fast and accurate retinal identification system: Using retinal blood vasculature landmarks | |
| Barzegar et al. | A new approach for iris localization in iris recognition systems | |
| KR101021134B1 (en) | Apparatus and methode for extracting the direction of fingerprint | |
| Guo et al. | Iris extraction based on intensity gradient and texture difference | |
| He et al. | A novel iris segmentation method for hand-held capture device | |
| KR100397750B1 (en) | Realtime pupil detecting method for iris recognition | |
| Sisodia et al. | A conglomerate technique for finger print recognition using phone camera captured images | |
| US10726259B2 (en) | Image processing method and system for iris recognition | |
| Zaim et al. | A robust and accurate segmentation of iris images using optimal partitioning | |
| CN113553890A (en) | Multi-modal biological feature fusion method and device, storage medium and equipment | |
| KR20040026905A (en) | Evaluation apparatus and method of image quality for realtime iris recognition, and storage media having program thereof | |
| Kyaw et al. | Performance analysis of features extraction on iris recognition system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |