CN106303000A - A kind of mobile terminal unlocked based on hand identification - Google Patents

A kind of mobile terminal unlocked based on hand identification Download PDF

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Publication number
CN106303000A
CN106303000A CN201610625959.3A CN201610625959A CN106303000A CN 106303000 A CN106303000 A CN 106303000A CN 201610625959 A CN201610625959 A CN 201610625959A CN 106303000 A CN106303000 A CN 106303000A
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palm
image
mobile terminal
module
point
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孟玲
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Individual
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Individual
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
    • H04M1/724—User interfaces specially adapted for cordless or mobile telephones
    • H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
    • H04M1/72463—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions to restrict the functionality of the device
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • 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
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1347—Preprocessing; Feature extraction
    • 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
    • G06V40/1365—Matching; Classification
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/66—Substation equipment, e.g. for use by subscribers with means for preventing unauthorised or fraudulent calling
    • H04M1/667—Preventing unauthorised calls from a telephone set
    • H04M1/67—Preventing unauthorised calls from a telephone set by electronic means
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • 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
    • G06V40/18—Eye characteristics, e.g. of the iris
    • 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
    • G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities

Abstract

The invention provides a kind of mobile terminal unlocked based on hand identification, including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, mobile terminal sound module and mobile terminal wireless network module.Mobile terminal memory module of the present invention for sending the preservation of information and reception information and situation information at that time, indispensable verification etc..

Description

A kind of mobile terminal unlocked based on hand identification
Technical field
The present invention relates to field of mobile terminals, be specifically related to a kind of mobile terminal unlocked based on hand identification.
Background technology
Mobile terminal greatly facilitates the life of people, and the most current mobile terminal is many does not possess identification Function.
Along with the constantly maturation of the technology of identification and developing rapidly of computer technology, various lifes based on human body physiological characteristics Thing technology has gradually incorporated the every aspect in life.Staff is the mark of human evolution, and people usually goes impression and touching with hands The world.Hands, unlike the eyes of people, easily produces baffled worry and fear when in the face of strange instrument, when gathering hand-characteristic To the infringement brought on human psychological compared with gathering and being positioned at the feature of eye negligible.In hand-characteristic research, opponent Palm properties study is the most important research direction.
Summary of the invention
For solving the problems referred to above, it is desirable to provide a kind of mobile terminal unlocked based on hand identification.
The purpose of the present invention realizes by the following technical solutions:
A kind of mobile terminal unlocked based on hand identification, including mobile terminal and the hand identification that is connected with mobile terminal Device, is characterized in that, described mobile terminal includes: controller, mobile terminal GIS module, information of mobile terminal acquisition module, shifting Dynamic terminal sending module, mobile terminal receiver module, mobile terminal sound module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
The invention have the benefit that mobile terminal achieve make an inspection tour policeman position location, the transmission of information, information Receive, can be real-time understand situation residing for active user；Mobile terminal memory module achieves transmission information and reception information And the preservation of situation information at that time, indispensable verification etc..
Accompanying drawing explanation
The invention will be further described to utilize accompanying drawing, but the embodiment in accompanying drawing does not constitute any limit to the present invention System, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain according to the following drawings Other accompanying drawing.
Fig. 1 is mobile terminal schematic diagram of the present invention；
Fig. 2 is the structural representation of hand identification device of the present invention.
Reference:
Iris identification device 1, image password data base 21, palm image acquisition module 22, palm image pre-processing module 23, palm image characteristics extraction module 24, palm characteristics of image identification module 25, finger print acquisition module 31, fingerprint storage module 32, Fingerprint Processing Module 33.
Detailed description of the invention
The invention will be further described with the following Examples.
Application scenarios 1
See Fig. 1, Fig. 2, a kind of mobile terminal unlocked based on hand identification of an embodiment in this application scene, Including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, Mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, movement are eventually End voice module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
This preferred embodiment mobile terminal memory module achieves transmission information and reception information and situation information at that time Preserve, indispensable verification etc..
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
This preferred embodiment strengthens module communication.
Preferably, described iris identification device 1 includes image password data base 21, palm image acquisition module 22, palm Image pre-processing module 23, palm image characteristics extraction module 24 and palm characteristics of image identification module 25；Described image password Data base 21 is for prestoring the palm characteristics of image as image password that user sets；Described palm image acquisition module 22 for including palm palmmprint dominant line information by single collecting device collection and palm is quiet under 800nm near infrared light The palm image of arteries and veins information；Described palm image pre-processing module 23 is used for the palm image collected is carried out pretreatment, with Eliminate and gather the impact that in palm image process, palm rotates, translates, and position the effective coverage of palm image characteristics extraction；Institute State palm image characteristics extraction module 24 for extracting the palm characteristics of image to be identified of pretreated palm image, and by institute State palm characteristics of image to be identified to be transported in described palm characteristics of image identification module 25 carry out feature identification；Described palm figure As feature recognition module 25 using in described palm characteristics of image to be identified and image password data base 21 as image password Palm characteristics of image contrasts, it determines palm characteristics of image to be identified with the described palm characteristics of image as image password is No unanimously.
This preferred embodiment is perfect iris identification device 1, uses palm characteristics of image as image password, the peace of system Full property is higher.
Preferably, the described palm image to collecting carries out pretreatment, including:
(1) palm image is carried out medium filtering process, after removing the system noise of palm image, build palm image Grey value histograms, palm image is carried out by the local minimum choosing predetermined gray value threshold range according to grey value histograms Binary conversion treatment；
(2) build four finger profile diagrams, extract forefinger and middle finger, nameless and little thumb in the palm image after binary conversion treatment Refer to anchor point at two, according to two anchor points, the palm image after binary conversion treatment is done rotation processing, to correct palm figure image position Put；At described two, anchor point is set as on forefinger lower boundary and the point of interface of middle finger coboundary and nameless lower boundary and little finger The point of interface on border, coordinate is followed successively by (v1,μ1)、(v2,μ2)；According to the anchor point calculating anglec of rotation:
θ = γ arctan v 2 - v 1 μ 2 - μ 1
In formula, γ is the Dynamic gene set, and span is set as [0.98,1.02]；
During θ ＞ 0, the palm image after binary conversion treatment is turned clockwise by the anglec of rotation calculated, during θ ＜ 0, Palm image after binary conversion treatment is rotated, during θ=0, not to binary conversion treatment counterclockwise by the anglec of rotation calculated After palm image do any rotation.
(3) from the palm image after correction, extract suitable centre of the palm reference point, set up a reference frame, location The effective coverage of palm image characteristics extraction；Select near remaining four border circular areas referring to root referred in addition to thumb as fixed The effective coverage of position palm image characteristics extraction, selects the center of circle of described border circular areas as centre of the palm reference point；Described circle Territory is carried out really by the finger root point referring to root point, middle finger and the third finger and the nameless finger root point with little finger of forefinger with middle finger Fixed, particularly as follows:
1) palm contours extract is carried out: using pixel each in palm image as central pixel point, calculate center respectively Pixel and the gray scale difference of 8 neighborhood territory pixel points, when central pixel point is positioned on palm profile, it is positioned at vertical palm profile Point outer on direction will be for maximum, by the pole of pixel gray scale difference each in judging regional area with central pixel point gray scale difference Big value finds the real palm profile point in palm image, so that it is determined that palm profile；
2) fingertip location of forefinger, middle finger, the third finger and little finger is determined: finger tip direction is defined as the side of palm To, Fingers to the right, determines the fingertip location of forefinger, middle finger, the third finger and little finger, the fingertip location position of wherein said middle finger Low order end in whole profile；
3) forefinger is extracted with middle finger, middle finger with the nameless and nameless finger root point with little finger: set up objective contour Parametrization equation: for given objective contour L (t), its arc length parameterized equation is expressed as L (t)=(x (t), y (t)), Wherein x (t) and y (t) represents the coordinate of profile point respectively, and t represents the parameter of contour curve equation, and t ∈ [0,1]；
Calculate curvature k (t) of contour curve, from middle fingertip, extend to both sides, first extended to forefinger direction The point that individual Curvature varying is big, is designated as S1, it is the seam points of forefinger and middle finger；First curvature extended to nameless direction becomes Change big point, be designated as W1, it is middle finger and nameless seam points；Continue to extend and obtain second big point of Curvature varying, note For W2, it is the nameless seam points with little finger；The point that described Curvature varying is big, refers to its curvature value and previous curvature value difference Point more than 2；
From a S1Set out, it is assumed that webs line any pixel point P1, find its and and P vertical with webs direction1Two pictures of distance 2 P that element is wide2And P3, calculate P respectively1With P2、P3Grad, using two Grad and SUM as evaluate P1Vertically Graded amount on webs direction, when SUM changes greatly, former point is forefinger and refers to root point Q with middle finger1；In like manner, middle finger and nothing Name refers to root point Q2, nameless refer to root point Q with little finger3；Described SUM changes greatly, refers to that its changing value is more than 2；
4) extraction refers to that root is round: junction point Q1And Q2, Q2And Q3, cross Q respectively1Q2And Q2Q3Make perpendicular bisector, intersect at a little (m n), is the center of circle of required border circular areas, O point and Q to O1Distance is the radius R of required border circular areas.
This preferred embodiment carries out medium filtering process to palm image, it is to avoid the noise spot of palm image causes image fixed Position inaccurate, then carries out binary conversion treatment to palm image, so that the palm area in palm image and background area Preferably separate；The position of palm image is carried out rotation correction process, decreases the rotation of introducing in image acquisition process, put down The impact of the factors such as shifting, proportional zoom；By extracting suitable reference point, set up new reference frame, position palm figure Effective coverage as feature extraction, it is possible to reduce the difficulty of palm characteristics of image identification, improve the robust of match cognization algorithm Property.
Preferably, the palm characteristics of image to be identified of described extraction pretreated palm image, including:
(1) using the bifurcation of the palm vein in pretreated palm image and palmmprint main line as palm figure to be identified Each characteristic point F as featurei(x, y), i=1,2 ... N, wherein N is characterized a number；By characteristic point to described border circular areas The ratio of the diameter of the distance in the center of circle and described border circular areas is as fisrt feature:
Y i = ( x i - m ) 2 + ( y i - n ) 2 2 R
In formula, YiRepresent the fisrt feature of ith feature point, (xi,yi) represent ith feature point coordinate；
The center of circle of described border circular areas is referred to root point Q with middle finger and the third finger2Line as datum line, datum line direction Be 0 degree, the line in characteristic point and the center of circle clockwise to the angle folded by datum line as second feature；
In formula, EiRepresent the second feature of ith feature point, EiSpan be 0 to 360 degree, (xi,yi) represent i-th The coordinate of individual characteristic point；
(2) using the fisrt feature of characteristic point as abscissa, second feature, as vertical coordinate, constructs coordinate system, by described Palm vein and palmmprint main line bifurcation project in coordinate system, and the two-dimensional feature vector setting up pretreated palm image is empty Between.
This preferred embodiment selects palm vein and palmmprint main line bifurcation as each spy of palm characteristics of image to be identified Levy a little, both considered the memory space of iris identification device 1 and the restriction of the speed of service, reflect again palm vein and palmmprint Change, the palm characteristics of image degree of accuracy to be identified of extraction is high, and extraction rate is fast.
Preferably, described palm characteristics of image identification module 25 is by described palm characteristics of image to be identified and image password number When contrasting according to the palm characteristics of image as image password in storehouse 21, by the two dimensional character of palm characteristics of image to be identified Vector space and the described distribution as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Carry out similarity comparison, particularly as follows: set the characteristic point in the two-dimensional feature vector space contrasting palm characteristics of image to be identified as treating Identifying characteristic point, described is standard as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Characteristic point, carries out overlapping by palm image to be identified with the palm image in image password data base 21, and described as figure The standard feature point corresponding to characteristic point to be identified is determined in the two-dimensional feature vector space in the palm characteristics of image of password, Judge that characteristic point to be identified is less than predeterminable range threshold value and true according to judged result with the distance of corresponding standard feature point Fixed palm characteristics of image to be identified is the most consistent with the described palm characteristics of image as image password.
This preferred embodiment sets palm characteristics of image identification module 25 and is identified palm characteristics of image to be identified Time concrete operations, practical convenient.
This application scene Dynamic gene γ value to setting is as 0.98, and the accuracy of identification of mobile terminal improves relatively 5%, recognition speed improves 8% relatively.
Application scenarios 2
See Fig. 1, Fig. 2, a kind of mobile terminal unlocked based on hand identification of an embodiment in this application scene, Including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, Mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, movement are eventually End voice module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
This preferred embodiment mobile terminal memory module achieves transmission information and reception information and situation information at that time Preserve, indispensable verification etc..
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
This preferred embodiment strengthens module communication.
Preferably, described iris identification device 1 includes image password data base 21, palm image acquisition module 22, palm Image pre-processing module 23, palm image characteristics extraction module 24 and palm characteristics of image identification module 25；Described image password Data base 21 is for prestoring the palm characteristics of image as image password that user sets；Described palm image acquisition module 22 for including palm palmmprint dominant line information by single collecting device collection and palm is quiet under 800nm near infrared light The palm image of arteries and veins information；Described palm image pre-processing module 23 is used for the palm image collected is carried out pretreatment, with Eliminate and gather the impact that in palm image process, palm rotates, translates, and position the effective coverage of palm image characteristics extraction；Institute State palm image characteristics extraction module 24 for extracting the palm characteristics of image to be identified of pretreated palm image, and by institute State palm characteristics of image to be identified to be transported in described palm characteristics of image identification module 25 carry out feature identification；Described palm figure As feature recognition module 25 using in described palm characteristics of image to be identified and image password data base 21 as image password Palm characteristics of image contrasts, it determines palm characteristics of image to be identified with the described palm characteristics of image as image password is No unanimously.
This preferred embodiment is perfect iris identification device 1, uses palm characteristics of image as image password, the peace of system Full property is higher.
Preferably, the described palm image to collecting carries out pretreatment, including:
(1) palm image is carried out medium filtering process, after removing the system noise of palm image, build palm image Grey value histograms, palm image is carried out by the local minimum choosing predetermined gray value threshold range according to grey value histograms Binary conversion treatment；
(2) build four finger profile diagrams, extract forefinger and middle finger, nameless and little thumb in the palm image after binary conversion treatment Refer to anchor point at two, according to two anchor points, the palm image after binary conversion treatment is done rotation processing, to correct palm figure image position Put；At described two, anchor point is set as on forefinger lower boundary and the point of interface of middle finger coboundary and nameless lower boundary and little finger The point of interface on border, coordinate is followed successively by (v1,μ1)、(v2,μ2)；According to the anchor point calculating anglec of rotation:
θ = γ arctan v 2 - v 1 μ 2 - μ 1
In formula, γ is the Dynamic gene set, and span is set as [0.98,1.02]；
During θ ＞ 0, the palm image after binary conversion treatment is turned clockwise by the anglec of rotation calculated, during θ ＜ 0, Palm image after binary conversion treatment is rotated, during θ=0, not to binary conversion treatment counterclockwise by the anglec of rotation calculated After palm image do any rotation.
(3) from the palm image after correction, extract suitable centre of the palm reference point, set up a reference frame, location The effective coverage of palm image characteristics extraction；Select near remaining four border circular areas referring to root referred in addition to thumb as fixed The effective coverage of position palm image characteristics extraction, selects the center of circle of described border circular areas as centre of the palm reference point；Described circle Territory is carried out really by the finger root point referring to root point, middle finger and the third finger and the nameless finger root point with little finger of forefinger with middle finger Fixed, particularly as follows:
1) palm contours extract is carried out: using pixel each in palm image as central pixel point, calculate center respectively Pixel and the gray scale difference of 8 neighborhood territory pixel points, when central pixel point is positioned on palm profile, it is positioned at vertical palm profile Point outer on direction will be for maximum, by the pole of pixel gray scale difference each in judging regional area with central pixel point gray scale difference Big value finds the real palm profile point in palm image, so that it is determined that palm profile；
2) fingertip location of forefinger, middle finger, the third finger and little finger is determined: finger tip direction is defined as the side of palm To, Fingers to the right, determines the fingertip location of forefinger, middle finger, the third finger and little finger, the fingertip location position of wherein said middle finger Low order end in whole profile；
3) forefinger is extracted with middle finger, middle finger with the nameless and nameless finger root point with little finger: set up objective contour Parametrization equation: for given objective contour L (t), its arc length parameterized equation is expressed as L (t)=(x (t), y (t)), Wherein x (t) and y (t) represents the coordinate of profile point respectively, and t represents the parameter of contour curve equation, and t ∈ [0,1]；
Calculate curvature k (t) of contour curve, from middle fingertip, extend to both sides, first extended to forefinger direction The point that individual Curvature varying is big, is designated as S1, it is the seam points of forefinger and middle finger；First curvature extended to nameless direction becomes Change big point, be designated as W1, it is middle finger and nameless seam points；Continue to extend and obtain second big point of Curvature varying, note For W2, it is the nameless seam points with little finger；The point that described Curvature varying is big, refers to its curvature value and previous curvature value difference Point more than 2；
From a S1Set out, it is assumed that webs line any pixel point P1, find its and and P vertical with webs direction1Two pictures of distance 2 P that element is wide2And P3, calculate P respectively1With P2、P3Grad, using two Grad and SUM as evaluate P1Vertically Graded amount on webs direction, when SUM changes greatly, former point is forefinger and refers to root point Q with middle finger1；In like manner, middle finger and nothing Name refers to root point Q2, nameless refer to root point Q with little finger3；Described SUM changes greatly, refers to that its changing value is more than 2；
4) extraction refers to that root is round: junction point Q1And Q2, Q2And Q3, cross Q respectively1Q2And Q2Q3Make perpendicular bisector, intersect at a little (m n), is the center of circle of required border circular areas, O point and Q to O1Distance is the radius R of required border circular areas.
This preferred embodiment carries out medium filtering process to palm image, it is to avoid the noise spot of palm image causes image fixed Position inaccurate, then carries out binary conversion treatment to palm image, so that the palm area in palm image and background area Preferably separate；The position of palm image is carried out rotation correction process, decreases the rotation of introducing in image acquisition process, put down The impact of the factors such as shifting, proportional zoom；By extracting suitable reference point, set up new reference frame, position palm figure Effective coverage as feature extraction, it is possible to reduce the difficulty of palm characteristics of image identification, improve the robust of match cognization algorithm Property.
Preferably, the palm characteristics of image to be identified of described extraction pretreated palm image, including:
(1) using the bifurcation of the palm vein in pretreated palm image and palmmprint main line as palm figure to be identified Each characteristic point F as featurei(x, y), i=1,2 ... N, wherein N is characterized a number；By characteristic point to described border circular areas The ratio of the diameter of the distance in the center of circle and described border circular areas is as fisrt feature:
Y i = ( x i - m ) 2 + ( y i - n ) 2 2 R
In formula, YiRepresent the fisrt feature of ith feature point, (xi,yi) represent ith feature point coordinate；
The center of circle of described border circular areas is referred to root point Q with middle finger and the third finger2Line as datum line, datum line direction Be 0 degree, the line in characteristic point and the center of circle clockwise to the angle folded by datum line as second feature；
In formula, EiRepresent the second feature of ith feature point, EiSpan be 0 to 360 degree, (xi,yi) represent i-th The coordinate of individual characteristic point；
(2) using the fisrt feature of characteristic point as abscissa, second feature, as vertical coordinate, constructs coordinate system, by described Palm vein and palmmprint main line bifurcation project in coordinate system, and the two-dimensional feature vector setting up pretreated palm image is empty Between.
This preferred embodiment selects palm vein and palmmprint main line bifurcation as each spy of palm characteristics of image to be identified Levy a little, both considered the memory space of iris identification device 1 and the restriction of the speed of service, reflect again palm vein and palmmprint Change, the palm characteristics of image degree of accuracy to be identified of extraction is high, and extraction rate is fast.
Preferably, described palm characteristics of image identification module 25 is by described palm characteristics of image to be identified and image password number When contrasting according to the palm characteristics of image as image password in storehouse 21, by the two dimensional character of palm characteristics of image to be identified Vector space and the described distribution as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Carry out similarity comparison, particularly as follows: set the characteristic point in the two-dimensional feature vector space contrasting palm characteristics of image to be identified as treating Identifying characteristic point, described is standard as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Characteristic point, carries out overlapping by palm image to be identified with the palm image in image password data base 21, and described as figure The standard feature point corresponding to characteristic point to be identified is determined in the two-dimensional feature vector space in the palm characteristics of image of password, Judge that characteristic point to be identified is less than predeterminable range threshold value and true according to judged result with the distance of corresponding standard feature point Fixed palm characteristics of image to be identified is the most consistent with the described palm characteristics of image as image password.
This preferred embodiment sets palm characteristics of image identification module 25 and is identified palm characteristics of image to be identified Time concrete operations, practical convenient.
This application scene Dynamic gene γ value to setting is as 0.99, and the accuracy of identification of mobile terminal improves relatively 4.5%, recognition speed improves 7.6% relatively.
Application scenarios 3
See Fig. 1, Fig. 2, a kind of mobile terminal unlocked based on hand identification of an embodiment in this application scene, Including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, Mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, movement are eventually End voice module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
This preferred embodiment mobile terminal memory module achieves transmission information and reception information and situation information at that time Preserve, indispensable verification etc..
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
This preferred embodiment strengthens module communication.
Preferably, described iris identification device 1 includes image password data base 21, palm image acquisition module 22, palm Image pre-processing module 23, palm image characteristics extraction module 24 and palm characteristics of image identification module 25；Described image password Data base 21 is for prestoring the palm characteristics of image as image password that user sets；Described palm image acquisition module 22 for including palm palmmprint dominant line information by single collecting device collection and palm is quiet under 800nm near infrared light The palm image of arteries and veins information；Described palm image pre-processing module 23 is used for the palm image collected is carried out pretreatment, with Eliminate and gather the impact that in palm image process, palm rotates, translates, and position the effective coverage of palm image characteristics extraction；Institute State palm image characteristics extraction module 24 for extracting the palm characteristics of image to be identified of pretreated palm image, and by institute State palm characteristics of image to be identified to be transported in described palm characteristics of image identification module 25 carry out feature identification；Described palm figure As feature recognition module 25 using in described palm characteristics of image to be identified and image password data base 21 as image password Palm characteristics of image contrasts, it determines palm characteristics of image to be identified with the described palm characteristics of image as image password is No unanimously.
This preferred embodiment is perfect iris identification device 1, uses palm characteristics of image as image password, the peace of system Full property is higher.
Preferably, the described palm image to collecting carries out pretreatment, including:
(1) palm image is carried out medium filtering process, after removing the system noise of palm image, build palm image Grey value histograms, palm image is carried out by the local minimum choosing predetermined gray value threshold range according to grey value histograms Binary conversion treatment；
(2) build four finger profile diagrams, extract forefinger and middle finger, nameless and little thumb in the palm image after binary conversion treatment Refer to anchor point at two, according to two anchor points, the palm image after binary conversion treatment is done rotation processing, to correct palm figure image position Put；At described two, anchor point is set as on forefinger lower boundary and the point of interface of middle finger coboundary and nameless lower boundary and little finger The point of interface on border, coordinate is followed successively by (v1,μ1)、(v2,μ2)；According to the anchor point calculating anglec of rotation:
θ = γ arctan v 2 - v 1 μ 2 - μ 1
In formula, γ is the Dynamic gene set, and span is set as [0.98,1.02]；
During θ ＞ 0, the palm image after binary conversion treatment is turned clockwise by the anglec of rotation calculated, during θ ＜ 0, Palm image after binary conversion treatment is rotated, during θ=0, not to binary conversion treatment counterclockwise by the anglec of rotation calculated After palm image do any rotation.
(3) from the palm image after correction, extract suitable centre of the palm reference point, set up a reference frame, location The effective coverage of palm image characteristics extraction；Select near remaining four border circular areas referring to root referred in addition to thumb as fixed The effective coverage of position palm image characteristics extraction, selects the center of circle of described border circular areas as centre of the palm reference point；Described circle Territory is carried out really by the finger root point referring to root point, middle finger and the third finger and the nameless finger root point with little finger of forefinger with middle finger Fixed, particularly as follows:
1) palm contours extract is carried out: using pixel each in palm image as central pixel point, calculate center respectively Pixel and the gray scale difference of 8 neighborhood territory pixel points, when central pixel point is positioned on palm profile, it is positioned at vertical palm profile Point outer on direction will be for maximum, by the pole of pixel gray scale difference each in judging regional area with central pixel point gray scale difference Big value finds the real palm profile point in palm image, so that it is determined that palm profile；
2) fingertip location of forefinger, middle finger, the third finger and little finger is determined: finger tip direction is defined as the side of palm To, Fingers to the right, determines the fingertip location of forefinger, middle finger, the third finger and little finger, the fingertip location position of wherein said middle finger Low order end in whole profile；
3) forefinger is extracted with middle finger, middle finger with the nameless and nameless finger root point with little finger: set up objective contour Parametrization equation: for given objective contour L (t), its arc length parameterized equation is expressed as L (t)=(x (t), y (t)), Wherein x (t) and y (t) represents the coordinate of profile point respectively, and t represents the parameter of contour curve equation, and t ∈ [0,1]；
Calculate curvature k (t) of contour curve, from middle fingertip, extend to both sides, first extended to forefinger direction The point that individual Curvature varying is big, is designated as S1, it is the seam points of forefinger and middle finger；First curvature extended to nameless direction becomes Change big point, be designated as W1, it is middle finger and nameless seam points；Continue to extend and obtain second big point of Curvature varying, note For W2, it is the nameless seam points with little finger；The point that described Curvature varying is big, refers to its curvature value and previous curvature value difference Point more than 2；
From a S1Set out, it is assumed that webs line any pixel point P1, find its and and P vertical with webs direction1Two pictures of distance 2 P that element is wide2And P3, calculate P respectively1With P2、P3Grad, using two Grad and SUM as evaluate P1Vertically Graded amount on webs direction, when SUM changes greatly, former point is forefinger and refers to root point Q with middle finger1；In like manner, middle finger and nothing Name refers to root point Q2, nameless refer to root point Q with little finger3；Described SUM changes greatly, refers to that its changing value is more than 2；
4) extraction refers to that root is round: junction point Q1And Q2, Q2And Q3, cross Q respectively1Q2And Q2Q3Make perpendicular bisector, intersect at a little (m n), is the center of circle of required border circular areas, O point and Q to O1Distance is the radius R of required border circular areas.
This preferred embodiment carries out medium filtering process to palm image, it is to avoid the noise spot of palm image causes image fixed Position inaccurate, then carries out binary conversion treatment to palm image, so that the palm area in palm image and background area Preferably separate；The position of palm image is carried out rotation correction process, decreases the rotation of introducing in image acquisition process, put down The impact of the factors such as shifting, proportional zoom；By extracting suitable reference point, set up new reference frame, position palm figure Effective coverage as feature extraction, it is possible to reduce the difficulty of palm characteristics of image identification, improve the robust of match cognization algorithm Property.
Preferably, the palm characteristics of image to be identified of described extraction pretreated palm image, including:
(1) using the bifurcation of the palm vein in pretreated palm image and palmmprint main line as palm figure to be identified Each characteristic point F as featurei(x, y), i=1,2 ... N, wherein N is characterized a number；By characteristic point to described border circular areas The ratio of the diameter of the distance in the center of circle and described border circular areas is as fisrt feature:
Y i = ( x i - m ) 2 + ( y i - n ) 2 2 R
In formula, YiRepresent the fisrt feature of ith feature point, (xi,yi) represent ith feature point coordinate；
The center of circle of described border circular areas is referred to root point Q with middle finger and the third finger2Line as datum line, datum line direction Be 0 degree, the line in characteristic point and the center of circle clockwise to the angle folded by datum line as second feature；
In formula, EiRepresent the second feature of ith feature point, EiSpan be 0 to 360 degree, (xi,yi) represent i-th The coordinate of individual characteristic point；
(2) using the fisrt feature of characteristic point as abscissa, second feature, as vertical coordinate, constructs coordinate system, by described Palm vein and palmmprint main line bifurcation project in coordinate system, and the two-dimensional feature vector setting up pretreated palm image is empty Between.
This preferred embodiment selects palm vein and palmmprint main line bifurcation as each spy of palm characteristics of image to be identified Levy a little, both considered the memory space of iris identification device 1 and the restriction of the speed of service, reflect again palm vein and palmmprint Change, the palm characteristics of image degree of accuracy to be identified of extraction is high, and extraction rate is fast.
Preferably, described palm characteristics of image identification module 25 is by described palm characteristics of image to be identified and image password number When contrasting according to the palm characteristics of image as image password in storehouse 21, by the two dimensional character of palm characteristics of image to be identified Vector space and the described distribution as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Carry out similarity comparison, particularly as follows: set the characteristic point in the two-dimensional feature vector space contrasting palm characteristics of image to be identified as treating Identifying characteristic point, described is standard as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Characteristic point, carries out overlapping by palm image to be identified with the palm image in image password data base 21, and described as figure The standard feature point corresponding to characteristic point to be identified is determined in the two-dimensional feature vector space in the palm characteristics of image of password, Judge that characteristic point to be identified is less than predeterminable range threshold value and true according to judged result with the distance of corresponding standard feature point Fixed palm characteristics of image to be identified is the most consistent with the described palm characteristics of image as image password.
This preferred embodiment sets palm characteristics of image identification module 25 and is identified palm characteristics of image to be identified Time concrete operations, practical convenient.
This application scene Dynamic gene γ value to setting is as 1.00, and the accuracy of identification of mobile terminal improves relatively 6%, recognition speed improves 8.5% relatively.
Application scenarios 4
See Fig. 1, Fig. 2, a kind of mobile terminal unlocked based on hand identification of an embodiment in this application scene, Including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, Mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, movement are eventually End voice module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
This preferred embodiment mobile terminal memory module achieves transmission information and reception information and situation information at that time Preserve, indispensable verification etc..
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
This preferred embodiment strengthens module communication.
Preferably, described iris identification device 1 includes image password data base 21, palm image acquisition module 22, palm Image pre-processing module 23, palm image characteristics extraction module 24 and palm characteristics of image identification module 25；Described image password Data base 21 is for prestoring the palm characteristics of image as image password that user sets；Described palm image acquisition module 22 for including palm palmmprint dominant line information by single collecting device collection and palm is quiet under 800nm near infrared light The palm image of arteries and veins information；Described palm image pre-processing module 23 is used for the palm image collected is carried out pretreatment, with Eliminate and gather the impact that in palm image process, palm rotates, translates, and position the effective coverage of palm image characteristics extraction；Institute State palm image characteristics extraction module 24 for extracting the palm characteristics of image to be identified of pretreated palm image, and by institute State palm characteristics of image to be identified to be transported in described palm characteristics of image identification module 25 carry out feature identification；Described palm figure As feature recognition module 25 using in described palm characteristics of image to be identified and image password data base 21 as image password Palm characteristics of image contrasts, it determines palm characteristics of image to be identified with the described palm characteristics of image as image password is No unanimously.
This preferred embodiment is perfect iris identification device 1, uses palm characteristics of image as image password, the peace of system Full property is higher.
Preferably, the described palm image to collecting carries out pretreatment, including:
(1) palm image is carried out medium filtering process, after removing the system noise of palm image, build palm image Grey value histograms, palm image is carried out by the local minimum choosing predetermined gray value threshold range according to grey value histograms Binary conversion treatment；
(2) build four finger profile diagrams, extract forefinger and middle finger, nameless and little thumb in the palm image after binary conversion treatment Refer to anchor point at two, according to two anchor points, the palm image after binary conversion treatment is done rotation processing, to correct palm figure image position Put；At described two, anchor point is set as on forefinger lower boundary and the point of interface of middle finger coboundary and nameless lower boundary and little finger The point of interface on border, coordinate is followed successively by (v1,μ1)、(v2,μ2)；According to the anchor point calculating anglec of rotation:
θ = γ arctan v 2 - v 1 μ 2 - μ 1
In formula, γ is the Dynamic gene set, and span is set as [0.98,1.02]；
During θ ＞ 0, the palm image after binary conversion treatment is turned clockwise by the anglec of rotation calculated, during θ ＜ 0, Palm image after binary conversion treatment is rotated, during θ=0, not to binary conversion treatment counterclockwise by the anglec of rotation calculated After palm image do any rotation.
(3) from the palm image after correction, extract suitable centre of the palm reference point, set up a reference frame, location The effective coverage of palm image characteristics extraction；Select near remaining four border circular areas referring to root referred in addition to thumb as fixed The effective coverage of position palm image characteristics extraction, selects the center of circle of described border circular areas as centre of the palm reference point；Described circle Territory is carried out really by the finger root point referring to root point, middle finger and the third finger and the nameless finger root point with little finger of forefinger with middle finger Fixed, particularly as follows:
1) palm contours extract is carried out: using pixel each in palm image as central pixel point, calculate center respectively Pixel and the gray scale difference of 8 neighborhood territory pixel points, when central pixel point is positioned on palm profile, it is positioned at vertical palm profile Point outer on direction will be for maximum, by the pole of pixel gray scale difference each in judging regional area with central pixel point gray scale difference Big value finds the real palm profile point in palm image, so that it is determined that palm profile；
2) fingertip location of forefinger, middle finger, the third finger and little finger is determined: finger tip direction is defined as the side of palm To, Fingers to the right, determines the fingertip location of forefinger, middle finger, the third finger and little finger, the fingertip location position of wherein said middle finger Low order end in whole profile；
3) forefinger is extracted with middle finger, middle finger with the nameless and nameless finger root point with little finger: set up objective contour Parametrization equation: for given objective contour L (t), its arc length parameterized equation is expressed as L (t)=(x (t), y (t)), Wherein x (t) and y (t) represents the coordinate of profile point respectively, and t represents the parameter of contour curve equation, and t ∈ [0,1]；
Calculate curvature k (t) of contour curve, from middle fingertip, extend to both sides, first extended to forefinger direction The point that individual Curvature varying is big, is designated as S1, it is the seam points of forefinger and middle finger；First curvature extended to nameless direction becomes Change big point, be designated as W1, it is middle finger and nameless seam points；Continue to extend and obtain second big point of Curvature varying, note For W2, it is the nameless seam points with little finger；The point that described Curvature varying is big, refers to its curvature value and previous curvature value difference Point more than 2；
From a S1Set out, it is assumed that webs line any pixel point P1, find its and and P vertical with webs direction1Two pictures of distance 2 P that element is wide2And P3, calculate P respectively1With P2、P3Grad, using two Grad and SUM as evaluate P1Vertically Graded amount on webs direction, when SUM changes greatly, former point is forefinger and refers to root point Q with middle finger1；In like manner, middle finger and nothing Name refers to root point Q2, nameless refer to root point Q with little finger3；Described SUM changes greatly, refers to that its changing value is more than 2；
4) extraction refers to that root is round: junction point Q1And Q2, Q2And Q3, cross Q respectively1Q2And Q2Q3Make perpendicular bisector, intersect at a little (m n), is the center of circle of required border circular areas, O point and Q to O1Distance is the radius R of required border circular areas.
This preferred embodiment carries out medium filtering process to palm image, it is to avoid the noise spot of palm image causes image fixed Position inaccurate, then carries out binary conversion treatment to palm image, so that the palm area in palm image and background area Preferably separate；The position of palm image is carried out rotation correction process, decreases the rotation of introducing in image acquisition process, put down The impact of the factors such as shifting, proportional zoom；By extracting suitable reference point, set up new reference frame, position palm figure Effective coverage as feature extraction, it is possible to reduce the difficulty of palm characteristics of image identification, improve the robust of match cognization algorithm Property.
Preferably, the palm characteristics of image to be identified of described extraction pretreated palm image, including:
(1) using the bifurcation of the palm vein in pretreated palm image and palmmprint main line as palm figure to be identified Each characteristic point F as featurei(x, y), i=1,2 ... N, wherein N is characterized a number；By characteristic point to described border circular areas The ratio of the diameter of the distance in the center of circle and described border circular areas is as fisrt feature:
Y i = ( x i - m ) 2 + ( y i - n ) 2 2 R
In formula, YiRepresent the fisrt feature of ith feature point, (xi,yi) represent ith feature point coordinate；
The center of circle of described border circular areas is referred to root point Q with middle finger and the third finger2Line as datum line, datum line direction Be 0 degree, the line in characteristic point and the center of circle clockwise to the angle folded by datum line as second feature；
In formula, EiRepresent the second feature of ith feature point, EiSpan be 0 to 360 degree, (xi,yi) represent i-th The coordinate of individual characteristic point；
(2) using the fisrt feature of characteristic point as abscissa, second feature, as vertical coordinate, constructs coordinate system, by described Palm vein and palmmprint main line bifurcation project in coordinate system, and the two-dimensional feature vector setting up pretreated palm image is empty Between.
This preferred embodiment selects palm vein and palmmprint main line bifurcation as each spy of palm characteristics of image to be identified Levy a little, both considered the memory space of iris identification device 1 and the restriction of the speed of service, reflect again palm vein and palmmprint Change, the palm characteristics of image degree of accuracy to be identified of extraction is high, and extraction rate is fast.
Preferably, described palm characteristics of image identification module 25 is by described palm characteristics of image to be identified and image password number When contrasting according to the palm characteristics of image as image password in storehouse 21, by the two dimensional character of palm characteristics of image to be identified Vector space and the described distribution as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Carry out similarity comparison, particularly as follows: set the characteristic point in the two-dimensional feature vector space contrasting palm characteristics of image to be identified as treating Identifying characteristic point, described is standard as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Characteristic point, carries out overlapping by palm image to be identified with the palm image in image password data base 21, and described as figure The standard feature point corresponding to characteristic point to be identified is determined in the two-dimensional feature vector space in the palm characteristics of image of password, Judge that characteristic point to be identified is less than predeterminable range threshold value and true according to judged result with the distance of corresponding standard feature point Fixed palm characteristics of image to be identified is the most consistent with the described palm characteristics of image as image password.
This preferred embodiment sets palm characteristics of image identification module 25 and is identified palm characteristics of image to be identified Time concrete operations, practical convenient.
This application scene Dynamic gene γ value to setting is as 1.01, and the accuracy of identification of mobile terminal improves relatively 4.8%, recognition speed improves 7.5% relatively.
Application scenarios 5
See Fig. 1, Fig. 2, a kind of mobile terminal unlocked based on hand identification of an embodiment in this application scene, Including mobile terminal and the hand identification device that is connected with mobile terminal, it is characterized in that, described mobile terminal includes: controller, Mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module, movement are eventually End voice module and mobile terminal wireless network module.
Preferably, described mobile terminal also includes the language for memory mobile terminal voice module being connected with controller Message ceases, the mobile terminal memory module of the reception information of mobile terminal receiver module.
This preferred embodiment mobile terminal memory module achieves transmission information and reception information and situation information at that time Preserve, indispensable verification etc..
Preferably, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, movement Terminal receiver module is connected with mobile terminal wireless network module respectively.
This preferred embodiment strengthens module communication.
Preferably, described iris identification device 1 includes image password data base 21, palm image acquisition module 22, palm Image pre-processing module 23, palm image characteristics extraction module 24 and palm characteristics of image identification module 25；Described image password Data base 21 is for prestoring the palm characteristics of image as image password that user sets；Described palm image acquisition module 22 for including palm palmmprint dominant line information by single collecting device collection and palm is quiet under 800nm near infrared light The palm image of arteries and veins information；Described palm image pre-processing module 23 is used for the palm image collected is carried out pretreatment, with Eliminate and gather the impact that in palm image process, palm rotates, translates, and position the effective coverage of palm image characteristics extraction；Institute State palm image characteristics extraction module 24 for extracting the palm characteristics of image to be identified of pretreated palm image, and by institute State palm characteristics of image to be identified to be transported in described palm characteristics of image identification module 25 carry out feature identification；Described palm figure As feature recognition module 25 using in described palm characteristics of image to be identified and image password data base 21 as image password Palm characteristics of image contrasts, it determines palm characteristics of image to be identified with the described palm characteristics of image as image password is No unanimously.
This preferred embodiment is perfect iris identification device 1, uses palm characteristics of image as image password, the peace of system Full property is higher.
Preferably, the described palm image to collecting carries out pretreatment, including:
(1) palm image is carried out medium filtering process, after removing the system noise of palm image, build palm image Grey value histograms, palm image is carried out by the local minimum choosing predetermined gray value threshold range according to grey value histograms Binary conversion treatment；
(2) build four finger profile diagrams, extract forefinger and middle finger, nameless and little thumb in the palm image after binary conversion treatment Refer to anchor point at two, according to two anchor points, the palm image after binary conversion treatment is done rotation processing, to correct palm figure image position Put；At described two, anchor point is set as on forefinger lower boundary and the point of interface of middle finger coboundary and nameless lower boundary and little finger The point of interface on border, coordinate is followed successively by (v1,μ1)、(v2,μ2)；According to the anchor point calculating anglec of rotation:
θ = γ arctan v 2 - v 1 μ 2 - μ 1
In formula, γ is the Dynamic gene set, and span is set as [0.98,1.02]；
During θ ＞ 0, the palm image after binary conversion treatment is turned clockwise by the anglec of rotation calculated, during θ ＜ 0, Palm image after binary conversion treatment is rotated, during θ=0, not to binary conversion treatment counterclockwise by the anglec of rotation calculated After palm image do any rotation.
(3) from the palm image after correction, extract suitable centre of the palm reference point, set up a reference frame, location The effective coverage of palm image characteristics extraction；Select near remaining four border circular areas referring to root referred in addition to thumb as fixed The effective coverage of position palm image characteristics extraction, selects the center of circle of described border circular areas as centre of the palm reference point；Described circle Territory is carried out really by the finger root point referring to root point, middle finger and the third finger and the nameless finger root point with little finger of forefinger with middle finger Fixed, particularly as follows:
1) palm contours extract is carried out: using pixel each in palm image as central pixel point, calculate center respectively Pixel and the gray scale difference of 8 neighborhood territory pixel points, when central pixel point is positioned on palm profile, it is positioned at vertical palm profile Point outer on direction will be for maximum, by the pole of pixel gray scale difference each in judging regional area with central pixel point gray scale difference Big value finds the real palm profile point in palm image, so that it is determined that palm profile；
2) fingertip location of forefinger, middle finger, the third finger and little finger is determined: finger tip direction is defined as the side of palm To, Fingers to the right, determines the fingertip location of forefinger, middle finger, the third finger and little finger, the fingertip location position of wherein said middle finger Low order end in whole profile；
3) forefinger is extracted with middle finger, middle finger with the nameless and nameless finger root point with little finger: set up objective contour Parametrization equation: for given objective contour L (t), its arc length parameterized equation is expressed as L (t)=(x (t), y (t)), Wherein x (t) and y (t) represents the coordinate of profile point respectively, and t represents the parameter of contour curve equation, and t ∈ [0,1]；
Calculate curvature k (t) of contour curve, from middle fingertip, extend to both sides, first extended to forefinger direction The point that individual Curvature varying is big, is designated as S1, it is the seam points of forefinger and middle finger；First curvature extended to nameless direction becomes Change big point, be designated as W1, it is middle finger and nameless seam points；Continue to extend and obtain second big point of Curvature varying, note For W2, it is the nameless seam points with little finger；The point that described Curvature varying is big, refers to its curvature value and previous curvature value difference Point more than 2；
From a S1Set out, it is assumed that webs line any pixel point P1, find its and and P vertical with webs direction1Two pictures of distance 2 P that element is wide2And P3, calculate P respectively1With P2、P3Grad, using two Grad and SUM as evaluate P1Vertically Graded amount on webs direction, when SUM changes greatly, former point is forefinger and refers to root point Q with middle finger1；In like manner, middle finger and nothing Name refers to root point Q2, nameless refer to root point Q with little finger3；Described SUM changes greatly, refers to that its changing value is more than 2；
4) extraction refers to that root is round: junction point Q1And Q2, Q2And Q3, cross Q respectively1Q2And Q2Q3Make perpendicular bisector, intersect at a little (m n), is the center of circle of required border circular areas, O point and Q to O1Distance is the radius R of required border circular areas.
This preferred embodiment carries out medium filtering process to palm image, it is to avoid the noise spot of palm image causes image fixed Position inaccurate, then carries out binary conversion treatment to palm image, so that the palm area in palm image and background area Preferably separate；The position of palm image is carried out rotation correction process, decreases the rotation of introducing in image acquisition process, put down The impact of the factors such as shifting, proportional zoom；By extracting suitable reference point, set up new reference frame, position palm figure Effective coverage as feature extraction, it is possible to reduce the difficulty of palm characteristics of image identification, improve the robust of match cognization algorithm Property.
Preferably, the palm characteristics of image to be identified of described extraction pretreated palm image, including:
(1) using the bifurcation of the palm vein in pretreated palm image and palmmprint main line as palm figure to be identified Each characteristic point F as featurei(x, y), i=1,2 ... N, wherein N is characterized a number；By characteristic point to described border circular areas The ratio of the diameter of the distance in the center of circle and described border circular areas is as fisrt feature:
Y i = ( x i - m ) 2 + ( y i - n ) 2 2 R
In formula, YiRepresent the fisrt feature of ith feature point, (xi,yi) represent ith feature point coordinate；
The center of circle of described border circular areas is referred to root point Q with middle finger and the third finger2Line as datum line, datum line direction Be 0 degree, the line in characteristic point and the center of circle clockwise to the angle folded by datum line as second feature；
In formula, EiRepresent the second feature of ith feature point, EiSpan be 0 to 360 degree, (xi,yi) represent i-th The coordinate of individual characteristic point；
(2) using the fisrt feature of characteristic point as abscissa, second feature, as vertical coordinate, constructs coordinate system, by described Palm vein and palmmprint main line bifurcation project in coordinate system, and the two-dimensional feature vector setting up pretreated palm image is empty Between.
This preferred embodiment selects palm vein and palmmprint main line bifurcation as each spy of palm characteristics of image to be identified Levy a little, both considered the memory space of iris identification device 1 and the restriction of the speed of service, reflect again palm vein and palmmprint Change, the palm characteristics of image degree of accuracy to be identified of extraction is high, and extraction rate is fast.
Preferably, described palm characteristics of image identification module 25 is by described palm characteristics of image to be identified and image password number When contrasting according to the palm characteristics of image as image password in storehouse 21, by the two dimensional character of palm characteristics of image to be identified Vector space and the described distribution as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Carry out similarity comparison, particularly as follows: set the characteristic point in the two-dimensional feature vector space contrasting palm characteristics of image to be identified as treating Identifying characteristic point, described is standard as the characteristic point in the two-dimensional feature vector space in the palm characteristics of image of image password Characteristic point, carries out overlapping by palm image to be identified with the palm image in image password data base 21, and described as figure The standard feature point corresponding to characteristic point to be identified is determined in the two-dimensional feature vector space in the palm characteristics of image of password, Judge that characteristic point to be identified is less than predeterminable range threshold value and true according to judged result with the distance of corresponding standard feature point Fixed palm characteristics of image to be identified is the most consistent with the described palm characteristics of image as image password.
This preferred embodiment sets palm characteristics of image identification module 25 and is identified palm characteristics of image to be identified Time concrete operations, practical convenient.
This application scene Dynamic gene γ value to setting is as 1.02, and the accuracy of identification of mobile terminal improves relatively 5.2%, recognition speed improves 7% relatively.
Last it should be noted that, above example is only in order to illustrate technical scheme, rather than the present invention is protected Protecting the restriction of scope, although having made to explain to the present invention with reference to preferred embodiment, those of ordinary skill in the art should Work as understanding, technical scheme can be modified or equivalent, without deviating from the reality of technical solution of the present invention Matter and scope.

Claims (3)

1. the mobile terminal unlocked based on hand identification, fills including mobile terminal and the hand identification being connected with mobile terminal Putting, it is characterized in that, described mobile terminal includes: controller, mobile terminal GIS module, information of mobile terminal acquisition module, movement Terminal sending module, mobile terminal receiver module, mobile terminal sound module and mobile terminal wireless network module.
A kind of mobile terminal unlocked based on hand identification the most according to claim 1, is characterized in that, described mobile terminal Also include the voice messaging for memory mobile terminal voice module being connected with controller, the connecing of mobile terminal receiver module The mobile terminal memory module of collection of letters breath.
A kind of mobile terminal unlocked based on hand identification the most according to claim 2, is characterized in that, described mobile terminal GIS module, information of mobile terminal acquisition module, mobile terminal sending module, mobile terminal receiver module respectively with mobile terminal Wireless network module is connected.
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CN113936307A (en) * 2021-12-17 2022-01-14 北京圣点云信息技术有限公司 Vein image recognition method and device based on thin film sensor

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