CN104541286A - Infrared scanning algorithm for intelligent mobile terminal - Google Patents
Infrared scanning algorithm for intelligent mobile terminal Download PDFInfo
- Publication number
- CN104541286A CN104541286A CN201580000005.7A CN201580000005A CN104541286A CN 104541286 A CN104541286 A CN 104541286A CN 201580000005 A CN201580000005 A CN 201580000005A CN 104541286 A CN104541286 A CN 104541286A
- Authority
- CN
- China
- Prior art keywords
- vein
- point
- image
- group
- left end
- 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 claims abstract description 159
- 238000000034 method Methods 0.000 claims abstract description 23
- 239000003086 colorant Substances 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 230000008878 coupling Effects 0.000 claims description 3
- 238000010168 coupling process Methods 0.000 claims description 3
- 238000005859 coupling reaction Methods 0.000 claims description 3
- 239000000203 mixture Substances 0.000 abstract description 10
- 238000004891 communication Methods 0.000 abstract description 2
- 238000007781 pre-processing Methods 0.000 abstract 1
- 230000008901 benefit Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
- 238000010408 sweeping Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- 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
- G06V40/14—Vascular patterns
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
-
- G—PHYSICS
- 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
-
- G—PHYSICS
- 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
- G06V40/12—Fingerprints or palmprints
- G06V40/13—Sensors therefor
-
- G—PHYSICS
- 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
- G06V40/107—Static hand or arm
- G06V40/117—Biometrics derived from hands
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Biology (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Vascular Medicine (AREA)
- Collating Specific Patterns (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention is suitable for the field of electronic communication and provides an infrared scanning method for an intelligent mobile terminal. The method comprises the following steps: the mobile terminal obtains a vein picture of a finger of a user through infrared scanning, the vein picture is subjected to preprocessing operation and therefore a gray level image of the vein picture cam be obtained, a gray level image of a mixture image can be obtained by superposing the gray level image on a standard background image, a finger vein image can be obtained by processing the mixture iamge, and the technical solution provided by the invention is advantaged by high identifying precisoin.
Description
Technical field
The invention belongs to electronic communication field, particularly relate to a kind of infrared scan algorithm of intelligent mobile terminal.
Background technology
Mobile terminal or make mobile communication terminal refer to the computer equipment that can use in movement, the saying of broad sense comprises mobile phone, notebook, panel computer, POS even comprise vehicle-mounted computer.But refer to mobile phone in most cases or there is smart mobile phone and the panel computer of multiple application function.Intelligent mobile terminal refer to there is system can the terminal device of the corresponding application program of Intelligent Installation, be generally mobile phone and panel computer.
Existing intelligent terminal only can realize simple Intelligent infrared scan function, so its low precision identified, cannot reach the requirement of identification.
Summary of the invention
Embodiment of the present invention object is the infrared scan algorithm providing a kind of intelligent mobile terminal, solves the problem of the scanning accuracy difference of prior art.
The embodiment of the present invention is achieved in that a kind of infrared scan method of intelligent mobile terminal, and described method comprises:
101, mobile terminal infrared scan obtains the vein picture of user's finger;
102, this vein picture and pre-service are obtained the gray level image of vein picture;
103, to the gray level image obtaining vision-mix after gray level image superposition normal background image;
104, process is carried out to vision-mix and obtain finger vena network image;
The implementation method of described 102 and 103 is:
Select a bit arbitrarily in vein picture, the color of this point be designated as (R0, G0, I0), the color of the point that normal background image is corresponding with selected element is designated as (RS, GS, IS); The color (Rn, Gn, In) of the gray level image of vision-mix is specially:
Rn=255 is multiplied by the poor absolute value of RS and R0 deducts RS difference divided by 255;
Gn=255 is multiplied by the difference of absolute value divided by GS of GS and G0 difference;
In=255 is multiplied by the difference of absolute value divided by IS of IS and I0 difference; Formula (1)
The institute traveling through described vein picture a little, by formula (1) calculate to the gray level image of vision-mix; Wherein, R, G, I represent three primary colors; Standard picture is the equally distributed images of three primary colors.
Optionally, described method also comprises after 104:
Cardinal vein image in finger vena network image and point vein image, obtain first point of vein group between adjacent two cardinal veins, obtain every bar in first point of vein group and divide the length of vein, obtain cardinal vein image and standard scores vein image in standard IV image, obtain second point of vein group between adjacent two cardinal veins, obtain every bar in second point of vein group and divide the length of vein, the length of vein is divided by bar every in first point of vein group to divide the length of vein to mate with bar every in second point of vein group, matching degree exceedes two points of veins of setting threshold value to putting under in initial matching territory, two points of veins pair that matching degree is the highest are found out in initial matching territory, set two articles of points of the highest veins of matching degree to being the 4th point of vein and the 3rd point of vein, obtain the first angle value between the 4th point of connected cardinal vein of vein, obtain the second angle value between the 3rd point of connected cardinal vein of vein, as the first angle value is consistent with the second angle value, then determine that two points of veins that matching degree is the highest are to coupling, two points of veins that matching degree is the highest are divided in intermediate matching domain, then by the 4th point of vein overlap in point vein of the 3rd in first point of vein group and second point of vein group, obtain the distance between other point of vein left end point and the 3rd vein left end point in finger vena network image, record the first distance value group between every other point of vein image left end point and the 3rd vein image left end point, obtain the distance between other point of vein left end point and the 4th vein left end point in standard IV image, record the second distance value group between every other point of vein left end point and the 4th vein left end point, mate the first distance value group and second distance value group, the number as the first distance value group and second distance value group same distance value exceedes digital threshold, then determine finger vena network image and standard IV images match.
Optionally, the calculating of described matching degree comprises:
In matching degree=the first point vein group a point of vein length/the second point vein group in every bar divide the length * 100% of vein.
In embodiments of the present invention, the technical scheme that technical scheme provided by the invention provides provides a kind of brand-new sweeping scheme, improves the precision identified, so it has the high advantage of accuracy of identification by the scheme of superposition.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the scanning algorithm of a kind of intelligent mobile terminal provided by the invention.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
The specific embodiment of the invention provides a kind of infrared scan method of intelligent mobile terminal, and the method is completed by intelligent mobile terminal, as shown in Figure 1, comprising:
101, mobile terminal infrared scan obtains the vein picture of user's finger;
102, this vein picture and pre-service are obtained the gray level image of vein picture;
103, to the gray level image obtaining vision-mix after gray level image superposition normal background image;
104, process is carried out to vision-mix and obtain finger vena network image;
The concrete methods of realizing of above-mentioned 102 and 103 can be:
Select a bit arbitrarily in vein picture, the color of this point be designated as (R0, G0, I0), the color of the point that normal background image is corresponding with selected element is designated as (RS, GS, IS); The color (Rn, Gn, In) of the gray level image of vision-mix is specially:
Rn=255 is multiplied by the poor absolute value of RS and R0 deducts RS difference divided by 255;
Gn=255 is multiplied by the difference of absolute value divided by GS of GS and G0 difference;
In=255 is multiplied by the difference of absolute value divided by IS of IS and I0 difference; Formula (1)
The institute traveling through described vein picture a little, by formula (1) calculate to the gray level image of vision-mix; Wherein, R, G, I represent three primary colors; Standard picture is the equally distributed images of three primary colors.
Technical scheme provided by the invention provides a kind of brand-new scanning algorithm, vein scanning is increased in mobile terminal by it, gray-scale value interpolation normal background post processing of image is carried out to it and obtains finger vena network image, owing to having superposed normal background image, so the finger vena network image that its process obtains is more clear, accuracy of identification is high, and sets specific image zooming-out scheme, adds the extraction accuracy of picture.
Said method can also comprise after 104:
Cardinal vein image in finger vena network image and point vein image, obtain first point of vein group between adjacent two cardinal veins, obtain every bar in first point of vein group and divide the length of vein, obtain cardinal vein image and standard scores vein image in standard IV image, obtain second point of vein group between adjacent two cardinal veins, obtain every bar in second point of vein group and divide the length of vein, the length of vein is divided by bar every in first point of vein group to divide the length of vein to mate with bar every in second point of vein group, matching degree exceedes two points of veins of setting threshold value to putting under in initial matching territory, two points of veins pair that matching degree is the highest are found out in initial matching territory, set two articles of points of the highest veins of matching degree to being the 4th point of vein and the 3rd point of vein, obtain the first angle value between the 4th point of connected cardinal vein of vein, obtain the second angle value between the 3rd point of connected cardinal vein of vein, as the first angle value is consistent with the second angle value, then determine that two points of veins that matching degree is the highest are to coupling, two points of veins that matching degree is the highest are divided in intermediate matching domain, then by the 4th point of vein overlap in point vein of the 3rd in first point of vein group and second point of vein group, obtain the distance between other point of vein left end point and the 3rd vein left end point in finger vena network image, record the first distance value group between every other point of vein image left end point and the 3rd vein image left end point, obtain the distance between other point of vein left end point and the 4th vein left end point in standard IV image, record the second distance value group between every other point of vein left end point and the 4th vein left end point, mate the first distance value group and second distance value group, the number as the first distance value group and second distance value group same distance value exceedes digital threshold, then determine finger vena network image and standard IV images match.
This kind of method can extraordinaryly prevent finger venous image from rotating the impact produced, because in finger vena identification, rotation is the problem of very rare process, but for vein image, in any case it rotates, angle between its point of vein and cardinal vein cannot change, in addition, it is also to improve recognition effect that point vein extracted between two cardinal veins carries out first time comparison, because point vein between two group veins is general all collected complete, deviation can not be there is because collection is imperfect, after point vein finding a pair standard right, two points of veins are completely overlapping, just can rotate the impact brought by removal of images, prove by experiment, the hand vein recognition carried out under this kind of mode, extraordinary discrimination is had when the anglec of rotation less than 45 °.So it has the advantage improving accuracy of identification.
Optionally, the calculating of above-mentioned matching degree comprises: in matching degree=the first point vein group a point of vein length/the second point vein group in every bar divide the length * 100% of vein.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.
Claims (3)
1. an infrared scan method for intelligent mobile terminal, is characterized in that, described method comprises:
101, mobile terminal infrared scan obtains the vein picture of user's finger;
102, this vein picture and pre-service are obtained the gray level image of vein picture;
103, to the gray level image obtaining vision-mix after gray level image superposition normal background image;
104, process is carried out to vision-mix and obtain finger vena network image;
The implementation method of described 102 and 103 is:
Select a bit arbitrarily in vein picture, the color of this point be designated as (R0, G0, I0), the color of the point that normal background image is corresponding with selected element is designated as (RS, GS, IS); The color (Rn, Gn, In) of the gray level image of vision-mix is specially:
Rn=255 is multiplied by the poor absolute value of RS and R0 deducts RS difference divided by 255;
Gn=255 is multiplied by the difference of absolute value divided by GS of GS and G0 difference;
In=255 is multiplied by the difference of absolute value divided by IS of IS and I0 difference; Formula (1)
The institute traveling through described vein picture a little, by formula (1) calculate to the gray level image of vision-mix; Wherein, R, G, I represent three primary colors; Standard picture is the equally distributed images of three primary colors.
2. method according to claim 1, is characterized in that, described method also comprises after 104:
Cardinal vein image in finger vena network image and point vein image, obtain first point of vein group between adjacent two cardinal veins, obtain every bar in first point of vein group and divide the length of vein, obtain cardinal vein image and standard scores vein image in standard IV image, obtain second point of vein group between adjacent two cardinal veins, obtain every bar in second point of vein group and divide the length of vein, the length of vein is divided by bar every in first point of vein group to divide the length of vein to mate with bar every in second point of vein group, matching degree exceedes two points of veins of setting threshold value to putting under in initial matching territory, two points of veins pair that matching degree is the highest are found out in initial matching territory, set two articles of points of the highest veins of matching degree to being the 4th point of vein and the 3rd point of vein, obtain the first angle value between the 4th point of connected cardinal vein of vein, obtain the second angle value between the 3rd point of connected cardinal vein of vein, as the first angle value is consistent with the second angle value, then determine that two points of veins that matching degree is the highest are to coupling, two points of veins that matching degree is the highest are divided in intermediate matching domain, then by the 4th point of vein overlap in point vein of the 3rd in first point of vein group and second point of vein group, obtain the distance between other point of vein left end point and the 3rd vein left end point in finger vena network image, record the first distance value group between every other point of vein image left end point and the 3rd vein image left end point, obtain the distance between other point of vein left end point and the 4th vein left end point in standard IV image, record the second distance value group between every other point of vein left end point and the 4th vein left end point, mate the first distance value group and second distance value group, the number as the first distance value group and second distance value group same distance value exceedes digital threshold, then determine finger vena network image and standard IV images match.
3. method according to claim 2, is characterized in that, the calculating of described matching degree comprises:
In matching degree=the first point vein group a point of vein length/the second point vein group in every bar divide the length * 100% of vein.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2015/070795 WO2016112518A1 (en) | 2015-01-15 | 2015-01-15 | Infrared scanning algorithm for intelligent mobile terminal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104541286A true CN104541286A (en) | 2015-04-22 |
Family
ID=52855805
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201580000005.7A Pending CN104541286A (en) | 2015-01-15 | 2015-01-15 | Infrared scanning algorithm for intelligent mobile terminal |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN104541286A (en) |
| WO (1) | WO2016112518A1 (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040228511A1 (en) * | 2003-05-14 | 2004-11-18 | Jean Lienard | Method and apparatus for setting the contrast and brightness of radiographic images |
| CN101840511A (en) * | 2010-06-04 | 2010-09-22 | 哈尔滨工程大学 | Method for extracting, matching and recognizing characteristics of finger veins |
| CN101976332A (en) * | 2010-11-10 | 2011-02-16 | 中国船舶重工集团公司第七一○研究所 | Finger vein collection and identification method by means of multi-features |
| CN102222229A (en) * | 2011-07-28 | 2011-10-19 | 陈庆武 | Method for preprocessing finger vein images |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184528B (en) * | 2011-05-12 | 2012-09-26 | 中国人民解放军国防科学技术大学 | Low-quality finger vein image enhancement method |
| CN103886321A (en) * | 2014-02-26 | 2014-06-25 | 中国船舶重工集团公司第七一〇研究所 | Finger vein feature extraction method |
-
2015
- 2015-01-15 CN CN201580000005.7A patent/CN104541286A/en active Pending
- 2015-01-15 WO PCT/CN2015/070795 patent/WO2016112518A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040228511A1 (en) * | 2003-05-14 | 2004-11-18 | Jean Lienard | Method and apparatus for setting the contrast and brightness of radiographic images |
| CN101840511A (en) * | 2010-06-04 | 2010-09-22 | 哈尔滨工程大学 | Method for extracting, matching and recognizing characteristics of finger veins |
| CN101976332A (en) * | 2010-11-10 | 2011-02-16 | 中国船舶重工集团公司第七一○研究所 | Finger vein collection and identification method by means of multi-features |
| CN102222229A (en) * | 2011-07-28 | 2011-10-19 | 陈庆武 | Method for preprocessing finger vein images |
Non-Patent Citations (2)
| Title |
|---|
| 张芳芳: "红外和可见光图像融合算法的研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 王科俊: "基于相对距离和角度的手指静脉识别方法", 《华中科技大学学报》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2016112518A1 (en) | 2016-07-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9852510B2 (en) | Method and apparatus for dividing image area | |
| CN103679147A (en) | Method and device for identifying model of mobile phone | |
| CN105912912B (en) | A kind of terminal user ID login method and system | |
| CN104504120B (en) | A kind of similar pictures detection method and device | |
| EP3761187A1 (en) | Method and apparatus for matching multimedia resource, and storage medium and electronic device | |
| CN104331682A (en) | Automatic building identification method based on Fourier descriptor | |
| CN104063690A (en) | Identity authentication method based on face recognition technology, device thereof and system thereof | |
| Popplewell et al. | Multispectral iris recognition utilizing hough transform and modified LBP | |
| CN104408741A (en) | Video global motion estimation method with sequential consistency constraint | |
| CN105574398A (en) | Verification code verification method and device | |
| CN103577813A (en) | Information fusion method for heterogeneous iris recognition | |
| CN103488966A (en) | Intelligent mobile phone capable of identifying real-name ticket information | |
| CN103886238A (en) | Account login method and device based on palm prints | |
| Gao et al. | The robustness of face-based CAPTCHAs | |
| CN108171229A (en) | A kind of recognition methods of hollow adhesion identifying code and system | |
| CN107862259A (en) | Human image collecting method and device, terminal installation and computer-readable recording medium | |
| CN104424485A (en) | Method and device for obtaining specific information based on image recognition | |
| CN104036272A (en) | Text detection method and electronic device | |
| US20180336243A1 (en) | Image Search Method, Apparatus and Storage Medium | |
| CN110852150B (en) | Face verification method, system, equipment and computer readable storage medium | |
| CN104541286A (en) | Infrared scanning algorithm for intelligent mobile terminal | |
| CN112560554A (en) | Lip language-based living body detection method, device and storage medium | |
| Gupta et al. | Sequenced tagged captcha: Generation and its analysis | |
| CN111079551B (en) | Finger vein recognition method and device based on singular value decomposition and storage medium | |
| CN110189273A (en) | A kind of hidden image restorative procedure based on double sampling |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150422 |