CN112069915A - ATM with face recognition system - Google Patents
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- CN112069915A CN112069915A CN202010819214.7A CN202010819214A CN112069915A CN 112069915 A CN112069915 A CN 112069915A CN 202010819214 A CN202010819214 A CN 202010819214A CN 112069915 A CN112069915 A CN 112069915A
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- 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
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- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- 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
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- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
- G07F19/20—Automatic teller machines [ATMs]
Abstract
The invention discloses an ATM with a face recognition system, belonging to the technical field of ATM, comprising a camera for automatically shooting the image of the ATM area and outputting the image to the face recognition system; the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs; and the verification system is used for inputting the information of the bank card and taking out cash from the ATM after the information is successfully verified by the face recognition system. By arranging the face recognition system in the ATM, the problem that the bank card and password information are leaked and the bank card and the password information are possibly stolen during the transaction process of transferring accounts, fetching money and the like on the ATM can be solved.
Description
Technical Field
The invention belongs to the technical field of ATM machines, and particularly relates to an ATM machine with a face recognition system.
Background
Authentication is a problem that people often encounter in daily life. Today, with the rapid development of electronic information technology, new requirements for the reliability and the mode of the identity card are provided in the fields of electronic commerce, internet banking, public security and the like, and the traditional identity verification method cannot meet the requirements. The human face as the facial feature has the characteristics of difficult counterfeiting, no loss and portability, and compared with other human body biological feature identification systems such as fingerprints, retinas, irises, genes and the like, the human face image identification is more direct and friendly, and a user has no psychological barrier.
With the development of artificial intelligence and scientific technology, living body verification is applied in various aspects, because the face of a person is an external attribute, the face image of the person is easily acquired by other people, and a common face recognition algorithm is used for extracting features from the face image and further comparing the face, if a precautionary measure is not taken, a face recognition system is easily deceived, and common deceptive measures comprise photos, video playback, a three-dimensional (3D) face model, a 3D face mask or a headgear and the like.
In the prior art, a bank deposit user can withdraw cash by using a bank card and a password, and if the information of the bank card and the password is leaked, the situation that the bank card is stolen and swiped appears.
Disclosure of Invention
The invention aims to at least solve the technical problem that the existing bank card and password information are leaked to cause the bank card to be stolen when a user goes to a bank to take money.
In order to achieve the above object, the present invention provides an ATM having a face recognition system, comprising:
the camera is used for automatically shooting the image of the ATM area and outputting the image to the face recognition system;
the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs;
and the verification system is used for inputting bank card information and verifying through the face recognition system.
Further, the face recognition system includes:
the image acquisition unit is used for acquiring a first image and a second image through the image shot by the camera;
a background region identification unit, configured to identify a background region of the second image from which the human body region is removed;
and the picture identification unit is used for comparing the background area with the first image and judging whether an abnormal event occurs according to a comparison result.
Further, the picture identification unit is further configured to:
detecting human body characteristic points and characteristic points of the background area, and judging whether abnormal events occur or not by detecting distance change between the human body characteristic points and the characteristic points of the background area.
Further, the face recognition system includes:
the human body identification unit is used for identifying a human body area and a limb area and detecting the number of the human body and the limb and the relative position of the limb area and the human body area to judge whether an abnormal event occurs.
Further, the face recognition system includes:
and the electronic product identification unit is used for identifying whether a regular area exists around the human body and whether the human body is in the regular area to judge whether an abnormal event occurs.
Further, the face recognition system includes:
and the robot identification unit/3D model identification unit is used for identifying the eye region of the human body and acquiring the region information of the eye to judge whether an abnormal event occurs.
Further, the method also comprises the following steps:
the infrared sensor is used for detecting whether people exist in an ATM region, and the camera shoots images according to the detection result of the infrared sensor and outputs the images to the face recognition system.
Further, the method also comprises the following steps:
the LED lamp comprises an illuminating LED lamp and a directional LED lamp, the angle of the directional LED lamp is adjusted, the directional LED lamp emits flash light to the eye region of the robot, and the robot identification unit/3D model identification unit can acquire the information whether eyes have blinking actions and whether blinking is carried out within preset time after the eyes blink so as to judge whether abnormal events occur.
Further, the face recognition system includes:
and the face recognition unit is used for recognizing the face image characteristic points and comparing the face image characteristic points with the face characteristic points in the database to judge whether abnormal events occur.
Further, the face recognition system includes:
and the preprocessing unit is used for image graying, image filtering and denoising, image enhancement and image edge sharpening.
The invention has the beneficial effects that:
by arranging the face recognition system in the ATM, the problem that the bank card and password information are leaked and the bank card and the password information are possibly stolen in the process of handling business on the ATM is solved.
Furthermore, the image acquisition unit is used for acquiring a first image and a second image in the ATM region, the image identification unit is used for comparing the background region with the first image, whether the environments are the same or not can be accurately judged, and whether an abnormal event occurs or not is judged according to whether the environments are the same or not.
Further, the image recognition unit detects the human body feature points and the feature points of the background area, and judges whether an abnormal event occurs or not by detecting the distance change between the human body feature points and the feature points of the background area. False verification such as photos can be eliminated by detecting the distance change condition between the characteristic points.
Furthermore, the human body area and the limb area can be identified through the human body identification unit, whether redundant human bodies or limbs exist and whether the limb positions and the positions of the human bodies to be identified are abnormal or not can be accurately judged, and illegal persons can accurately judge that the illegal persons are illegal to verify if the illegal persons hold photos or electronic devices with hands.
Furthermore, the electronic product identification unit can be used for identifying whether a regular region exists around the human body and whether the human body is in the regular region to judge whether an abnormal event occurs, and can prevent lawless persons from playing videos by using electronic equipment to cheat the verification system by identifying whether the regular region exists around the human body and whether the human body is in the regular region, so that the lawless persons are likely to be in the cheating verification system if the human body is in the range of the regular region, and can judge that the lawless persons are verified.
Further, the robot recognition unit/3D model recognition unit can be used to recognize an eye region of a human body and acquire eye region information to determine whether an abnormal event occurs, and the 3D machine or the 3D model can be recognized by acquiring the eye region information.
Furthermore, the face recognition unit can be used for recognizing the face image feature points and comparing the face image feature points with the face characteristic points in the database to judge whether an abnormal event occurs.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
Fig. 1 is a schematic structural diagram showing an ATM with a face recognition system according to embodiment 1;
fig. 2 is a schematic structural diagram showing an ATM with a face recognition system according to embodiment 2;
fig. 3 shows a schematic structural diagram of an ATM with a face recognition system according to embodiment 3.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
An ATM having a face recognition system, comprising:
the camera is used for automatically shooting the image of the ATM area and outputting the image to the face recognition system;
the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs;
and the verification system is used for inputting the information of the bank card and verifying the information through the face recognition system.
The face recognition system is arranged in the ATM, so that the problem that the bank card and password information are leaked and the bank card and the password information are possibly embezzled in the process of transacting businesses such as transferring accounts, inquiring balance and getting money on the ATM can be solved.
In one example, the camera employs an array camera.
The array camera can shoot a wide visual field range, and the visual field range larger than 180 degrees can be obtained by combining with the detection equipment, so that whether other people play videos around the human body or cheat the verification system by using pictures and other modes can be identified during subsequent human body identification.
In one example, a verification system includes an input unit and a money payout unit.
In one example, the input unit is used for inserting a bank card or inputting a bank card number, inputting a money-taking password, inputting a money-taking amount and calling the face verification system for face verification.
In one example, the money pay unit is used to withdraw funds from the ATM after verification by the face recognition system.
As a preferable aspect, the face recognition system includes:
the image acquisition unit is used for acquiring a first image and a second image through an image shot by the camera;
the background area identification unit is used for identifying a background area of the second image after the human body area is removed;
and the picture identification unit is used for comparing the background area with the first image and judging whether an abnormal event occurs according to the comparison result.
It should be noted that, the human body in the present technical solution refers to a person to be detected for biometric authentication, and the human body area refers to all objects except the environment, including a human body and other objects, such as other human bodies, limbs, or objects carried by the human body.
The first image is acquired when no person is detected, the second image is acquired when a person enters a fixed scene, and whether the environment where the human body is located is the same as the fixed scene or not can be accurately judged by comparing the first image with the background area, so that whether an abnormal event occurs or not is judged. The first image is updated at intervals due to changes in the environment.
As a preferable solution, the picture identification unit is further configured to:
and detecting the human body characteristic points and the characteristic points of the background area, and judging whether abnormal events occur or not by detecting the distance change between the human body characteristic points and the characteristic points of the background area.
The human body characteristic points comprise the head, the shoulders, the arms, the hands, the shoulders and other parts, and the characteristic points of the background area comprise any part convenient to identify.
It should be noted that, because a plurality of characteristic points of the human body and the background region need to be found, a plurality of second images need to be obtained in the process, and the distance between the human body characteristic points in each second image and the distance between the human body characteristic points and the characteristic points of the background region in the second image are respectively detected; it should be understood by those skilled in the art that the normal human body and each part of the human body are in constant motion, and therefore the distances between each part of the human body and the feature points of the background region are also unequal and variable.
As a preferable aspect, the face recognition system includes:
and the human body identification unit is used for identifying the human body area and the limb area, detecting the number of the human body and the limb and the relative position of the limb area and the human body area and judging whether an abnormal event occurs.
It should be noted that the calculation method of the body region and the limb region is identified by using a convolutional neural network algorithm, and the body identification unit can judge whether redundant limbs appear or not and whether abnormal conditions appear at the positions of the limbs and the body region or not.
According to the technical scheme, whether other limbs except the human body exist is detected, and illegal verification is judged when the limbs have abnormal actions, for example, the hands of the other limbs are close to the human body, and the shoulders of the other limbs are far away from the human body, so that illegal persons can judge illegal verification if the hands cannot be shot when holding the picture or the electronic device with the hands.
As a preferable aspect, the face recognition system includes:
and the electronic product identification unit is used for identifying whether a regular area exists around the human body and whether the human body is in the regular area to judge whether an abnormal event occurs.
It should be noted that the rule area may be obtained by using an edge recognition algorithm, which is used to prevent a lawbreaker from playing a video using an electronic device to cheat the verification system, so that if a human body is within the rule area, the video is likely to be in the cheating verification system, and the illegal verification can be determined.
In one example, the regular region is one of a rectangular region, a square region, or a circular region, and the edges surrounding the regular region are alternately composed of a plurality of colors.
It should be noted that general electronic devices are regular in shape and have different colors even if the edge portions have the same color.
As a preferable aspect, the face recognition system includes:
and the robot identification unit/3D model identification unit is used for identifying the eye region of the human body and acquiring the region information of the eye to judge whether an abnormal event occurs.
The eye region information is whether blinking is performed or not and whether blinking is performed within a predetermined time after light stimulation is performed or not; if yes, the verification is passed, and if not, the verification is judged to be illegal.
Generally, a person can blink and other actions when being stimulated by light, and if the 3D robot is not influenced by strong light, the robot face or the 3D model can be eliminated through light stimulation.
In general, a person blinks due to conditioned reflex action when being subjected to light stimulation, and the blink start time is within a predetermined time after the light stimulation, it is determined whether the blinking starts within a predetermined time range after the light stimulation to prevent the verification of coincidence due to the simulated blinking of the robot. The method has the advantages that in the prior art, the identification is carried out by detecting the change of the pupil or the iris of the human eye, the human body needs to be close to the equipment by identifying the pupil or the iris, the shooting angle of the camera also needs to be parallel or aligned with the iris or the pupil, the identification requirement is higher, the requirement of the technical scheme on the inspection link by identifying the blinking action is low, the application range is wider, the detection is more accurate, and the method can be matched with other technical schemes to realize more accurate verification.
As a preferable scheme, the method further comprises the following steps: an infrared sensor is arranged on the base plate,
the infrared sensor is used for detecting whether people exist in the ATM area, the camera shoots images according to the detection result of the infrared sensor, and the images are output to the face recognition system.
As a preferable scheme, the method further comprises the following steps: the LED lamp comprises an illuminating LED lamp and a directional LED lamp, the directional LED lamp is adjusted in angle, flashing light is emitted to the eye region of the LED lamp, and the robot identification unit/3D model identification unit can acquire the blinking action of eyes and the blinking information within the preset time after the eye blinking to judge whether an abnormal event occurs.
The LED lamp is angle and focus adjustable LED lamp, has two uses here, when environmental information is darker, can use the LED lamp to send the astigmatism and throw light on, when being used for the human body to verify, makes the LED lamp send the parallel light and has directive property function.
As a preferable aspect, the face recognition system includes:
and the face recognition unit is used for recognizing the face image characteristic points and comparing the face image characteristic points with the face characteristic points in the database to judge whether abnormal events occur.
The face image feature points can comprise easily-recognized parts such as eyes, a nose, a mouth and the like, whether an abnormal event occurs can be judged by comparing the shot face image with the face image in the database stored in the ATM, and if the comparison result is the same, the verification is passed.
As a preferable aspect, the face recognition system includes:
the preprocessing unit is used for image graying, image filtering and denoising, image enhancement and image edge sharpening.
The preprocessing unit is used for preprocessing and denoising the image acquired by the image acquisition unit, so that the denoised image is clearer and more accurate.
Example 1
Referring to fig. 1, an ATM having a face recognition system includes a camera for automatically photographing an image of an area of the ATM and outputting the image to the face recognition system, a verification system, and a display; the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs; the verification system is used for inputting bank card information, performing verification through the face recognition system, handling the businesses such as transferring accounts and taking cash out of the ATM after the verification is successful; the display is used for displaying the information of the operation.
The face recognition system is arranged in the ATM, so that the problem that the bank card and password information are leaked and the bank card and the password information are possibly embezzled in the process of transacting businesses such as transferring accounts, inquiring balance and getting money on the ATM can be solved.
Example 2
Referring to fig. 2, an ATM having a face recognition system includes a camera for automatically photographing an image of an area of the ATM and outputting the image to the face recognition system, an infrared sensor, a face recognition system, a verification system, and a display; the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs; the verification system is used for inputting bank card information and verifying through the face recognition system, and services such as money taking and transfer can be handled after verification is successful; the display is used for displaying the information of the operation; the verification system comprises an input unit and a money-telling unit, wherein the input unit is used for inserting a bank card or inputting a bank card number, inputting a money-getting password, inputting money-getting amount and calling the face verification system to perform face verification; the money receiving unit is used for taking money from the ATM after the face recognition system verifies; the face recognition system comprises an image acquisition unit, a face recognition unit and a face recognition unit, wherein the image acquisition unit is used for acquiring a first image when no person exists in an ATM region and a second image when a person exists in the ATM region; the background area identification unit is used for identifying a background area of the second image after the human body area is removed; and the picture identification unit is used for comparing the acquired background area with the first image and judging whether an abnormal event occurs according to the comparison result.
The infrared sensor can be an infrared camera or a common infrared temperature sensor and is used for detecting whether an object close to the temperature of a human body exists in the ATM area or not, acquiring a first image when no person is detected, and acquiring a second image when a person enters the ATM area; the first image can be collected once at intervals, because the applied environment generally changes frequently, the environment picture needs to be updated regularly, the first image and the background area can be compared more accurately in the human body detection process, whether the environment where the human body is located is different from the fixed scene of the ATM area can be accurately judged, and whether an abnormal event occurs is judged.
Example 3
Referring to fig. 3, an ATM having a face recognition system includes an array camera, an infrared sensor, a face recognition system, a verification system, and a display, the camera is used to automatically capture an image of an area of the ATM and output the image to the face recognition system; the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs; the verification system is used for inputting bank card information and verifying through the face recognition system, and services such as money taking and transfer can be handled after verification is successful; the verification system comprises an input unit and a money-telling unit, wherein the input unit is used for inserting a bank card or inputting a bank card number, inputting a money-getting password, inputting money-getting amount and calling the face verification system to perform face verification; the money receiving unit is used for taking money from the ATM after the face recognition system verifies; the display is used for displaying the information of the operation; the face recognition system includes: the LED lamp comprises an LED lamp, a preprocessing unit, a processing unit and a storage unit, wherein the processing unit is used for processing various data operations, and the storage unit is used for storing processing programs, shot environment pictures and intermediate processed data; the face recognition system further comprises: the image acquisition unit is used for acquiring a first image when no person exists in the ATM area and a second image when a person exists in the ATM area; the background area identification unit is used for identifying a background area of the second image after the human body area is removed; and the picture identification unit is used for comparing the acquired background area with the first image and judging whether an abnormal event occurs according to the comparison result.
The array camera is used for shooting images, a wider visual field range can be shot by using the array camera, the visual field range larger than 180 degrees can be obtained by combining detection equipment, and therefore whether a person plays a video or a verification system is cheated by using a photo or other modes can be recognized during subsequent human body recognition; the infrared sensor can be an infrared camera or a common infrared temperature sensor and is used for detecting whether an object close to the temperature of a human body exists in an ATM area or not, if the object does not exist in the ATM area, the image acquisition unit acquires a first image, and if a person enters the ATM area, the image acquisition unit acquires a second image; the first image can be collected once at intervals, and because the applied environment generally changes frequently, the environment photo needs to be updated regularly, so that the first image and the background area can be compared more accurately in the human body detection process, whether the environment where the human body is located is different from the fixed scene of the ATM area can be accurately judged, and whether an abnormal event occurs or not can be judged; the processor is used for processing various data operations, and the memory is used for storing processing programs, shot pictures and intermediate processing data; the preprocessing unit is used for preprocessing and denoising the acquired image; the preprocessing unit is used for image graying, image filtering denoising, image enhancement, image edge sharpening and the like, so that a denoised image is clearer and more accurate; the LED lamp comprises an illuminating LED lamp and a directional LED lamp.
If the comparison result of the first image and the background area is normal, carrying out the next verification: the human body feature points and the feature points of the background area are detected through the identification unit, and whether abnormal events occur is judged by detecting the distance change between the human body feature points and the feature points of the background area.
The human body characteristic points comprise the head, the shoulders, the arms, the hands, the shoulders and other parts, and the characteristic points of the background area comprise any part convenient to identify; and acquiring a plurality of second images through an image acquisition unit, and comprehensively judging the distance change condition between the characteristic points by detecting the distance between each human body characteristic point and the distance between the human body characteristic point and the background area, and further judging whether an abnormal event occurs.
And detecting the distance between each characteristic point of the human body and the distance between the characteristic point of the human body image and the characteristic point of the background area, and if the change sizes of the distances between the characteristic points are not equal or most of the distances are not equal, the verification is passed.
It should be noted that: most of the distances are unequal, more than half the distances between feature points are unequal; for example, if there are 5 human body feature points and the number of feature points in the background area is 3, the number of distances between the human body feature points is C2 5The distance between the human body characteristic point and the characteristic point of the background area is 5X 3-15, the distance data between 25 characteristic points are totally obtained, and if the 25 distance data are different or more than half of the distance data are different, the verification is passed.
It should be noted that the background area refers to an environmental area where a human body is located, the human body area refers to all objects except the environment, including a detected human body and other objects, such as an extra human body, objects carried by the human body, or limbs, and the like; it should be understood by those skilled in the art that the normal human body and each part of the human body are in constant motion, and therefore the distances between each part of the human body and the feature points of the background region are also unequal and variable.
If the detection is normal, the next verification is carried out: the human body identification unit identifies the human body area and the limb area and detects the number of the human body and the limb and the relative position of the limb area and the human body area to judge whether an abnormal event occurs.
The calculation method of the human body area and the limb area is identified by adopting a convolutional neural network algorithm, and the human body identification unit can judge whether redundant limbs appear or not and whether abnormal conditions exist in the positions of the limbs and the human body area or not.
According to the technical scheme, whether other limbs except the human body exist is detected, and illegal verification is judged when the limbs have abnormal actions, for example, the part with the hand is close to the human body and the shoulder is far away from the human body, so that illegal persons can judge illegal verification if the illegal persons cannot shoot the hand when holding a picture or an electronic device with the hand.
If the detection is normal, the next verification is carried out: whether a regular area exists around the human body and whether the human body is in the regular area are identified through the electronic product identification unit to judge whether an abnormal event occurs, the regular area is one of a rectangular area, a square area or a circular area, and the edge of the regular area can be formed by alternately forming multiple colors.
It should be noted that the regular area can be obtained by using an edge recognition algorithm, general electronic devices are regular in shape, the edge part has the same color and also has different colors, and the step is used for preventing lawless persons from playing videos by using electronic equipment to cheat the verification system, so that if a human body is in the range of the regular area, the human body is likely to be in the cheating verification system, and the illegal verification can be judged.
If the detection is normal, the next verification is carried out:
and the robot identification unit/3D model identification unit is used for identifying the eye region of the human body and acquiring the region information of the eye to judge whether an abnormal event occurs.
The eye region information is whether blinking is performed or not and whether blinking is performed within a predetermined time after light stimulation is performed or not; if yes, the verification is passed, and if not, the verification is judged to be illegal.
Generally, a person can blink and other actions when being stimulated by light, and if the 3D robot is not influenced by strong light, the robot face or the 3D model can be eliminated through light stimulation.
In general, a person blinks due to conditioned reflex action when being subjected to light stimulation, and the blink start time is within a predetermined time after the light stimulation, it is determined whether the blinking starts within a predetermined time range after the light stimulation to prevent the verification of blink coincidence by the robot simulation. The method has the advantages that in the prior art, the identification is carried out by detecting the change of the pupil or the iris of the human eye, the human body needs to be close to the equipment by identifying the pupil or the iris, the shooting angle of the camera also needs to be parallel or aligned with the iris or the pupil, the identification requirement is higher, the requirement of the technical scheme on the inspection link by identifying the blinking action is low, the application range is wider, the detection is more accurate, and the method can be matched with other technical schemes to realize more accurate verification.
In this embodiment, the angle and the focus of LED lamp are all adjustable, have two uses, when environmental information is darker, can use the LED lamp to send astigmatism and throw light on, when being used for human body identification, the LED lamp sends the parallel light and has the directive property function, through the angle of adjusting directive property LED lamp, to its eye region transmission flash of light, robot identification unit/3D model recognition cell can acquire whether the eye has the action of blinking and whether the information of blinking is carried out in the predetermined time after the flash of light and is judged whether there is the abnormal event to take place.
If the detection is normal, the next step is carried out:
and the face recognition unit is used for recognizing the face image characteristic points and comparing the face image characteristic points with the face characteristic points in the database to judge whether abnormal events occur.
The face image feature points can comprise easily-recognized parts such as eyes, a nose, a mouth and the like, whether an abnormal event occurs can be judged by comparing the shot face image with the face image in the database stored in the ATM, and if the comparison result is the same, the verification is passed.
It should be noted that, if the above identification unit finds an abnormal event, the page returns to the original login page, and if all the abnormal events are normal, the authentication is passed, and then the transactions such as transfer or money taking can be performed.
In the embodiment, the human body is identified by adopting the five identification units, so that the means that lawbreakers can perform deception verification by using pictures, videos, robot/3D models and other modes in the prior art can be eliminated, the human body is identified more accurately, an expensive infrared camera is not required to be adopted in the technical scheme, the cost is saved, only a common camera and a common infrared sensor are used, and the economic effect is good.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (10)
1. An ATM having a face recognition system, comprising:
the camera is used for automatically shooting the image of the ATM area and outputting the image to the face recognition system;
the face recognition system is used for automatically recognizing the acquired image so as to judge whether an abnormal condition occurs;
and the verification system is used for inputting bank card information and verifying through the face recognition system.
2. An ATM having a face recognition system as recited in claim 1, wherein the face recognition system comprises:
the image acquisition unit is used for acquiring a first image and a second image through the image shot by the camera;
a background region identification unit, configured to identify a background region of the second image from which the human body region is removed;
and the picture identification unit is used for comparing the background area with the first image and judging whether an abnormal event occurs according to a comparison result.
3. An ATM having a face recognition system as recited in claim 2, wherein the picture recognition unit is further configured to:
detecting human body characteristic points and characteristic points of the background area, and judging whether abnormal events occur or not by detecting distance change between the human body characteristic points and the characteristic points of the background area.
4. An ATM having a face recognition system as recited in claim 1, wherein the face recognition system comprises:
the human body identification unit is used for identifying a human body area and a limb area and detecting the number of the human body and the limb and the relative position of the limb area and the human body area to judge whether an abnormal event occurs.
5. An ATM having a face recognition system as recited in claim 1, wherein the face recognition system comprises:
and the electronic product identification unit is used for identifying whether a regular area exists around the human body and whether the human body is in the regular area to judge whether an abnormal event occurs.
6. An ATM having a face recognition system as recited in claim 1, wherein the face recognition system comprises:
and the robot identification unit/3D model identification unit is used for identifying the eye region of the human body and acquiring the region information of the eye to judge whether an abnormal event occurs.
7. An ATM having a face recognition system as recited in claim 1, further comprising:
the infrared sensor is used for detecting whether people exist in an ATM region, and the camera shoots images according to the detection result of the infrared sensor and outputs the images to the face recognition system.
8. An ATM having a face recognition system as recited in claim 6, further comprising:
the LED lamp comprises an illuminating LED lamp and a directional LED lamp, the angle of the directional LED lamp is adjusted, the directional LED lamp emits flash light to the eye region of the robot, and the robot identification unit/3D model identification unit can acquire the information whether eyes have blinking actions and whether blinking is carried out within preset time after the eyes blink so as to judge whether abnormal events occur.
9. An ATM having a face recognition system as recited in claim 1, wherein the face recognition system comprises:
and the face recognition unit is used for recognizing the face image characteristic points and comparing the face image characteristic points with the face characteristic points in the database to judge whether abnormal events occur.
10. An ATM having a face recognition system as recited in claim 1, said face recognition system comprising:
and the preprocessing unit is used for image graying, image filtering and denoising, image enhancement and image edge sharpening.
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