CN111986135A

CN111986135A - Image anti-counterfeiting identification method, device, equipment and computer readable storage medium

Info

Publication number: CN111986135A
Application number: CN202010869149.9A
Authority: CN
Inventors: 李扬渊
Original assignee: Chengdu Ruigan Microelectronics Co ltd
Current assignee: Chengdu Ruigan Microelectronics Co ltd
Priority date: 2020-08-26
Filing date: 2020-08-26
Publication date: 2020-11-24

Abstract

The application provides an anti-counterfeiting identification method, an anti-counterfeiting identification device, an anti-counterfeiting identification equipment and a computer readable storage medium for determining whether a two-dimensional image of a collected target object is an image collected by a real object or not by combining a three-dimensional image, and can solve the problem that a fingerprint sleeve made of materials such as liquid glue and the like with colloid, water and electrolyte has high deception in the aspect of fingerprint identification in the prior art. The application provides an anti-counterfeiting identification method of an image, which comprises the following steps: acquiring a two-dimensional image and a three-dimensional image of a target object; detecting whether a preset three-dimensional image characteristic exists in the three-dimensional image, wherein the three-dimensional image characteristic is used for indicating the characteristic of the target object in the preset three-dimensional image; and if so, determining that the two-dimensional image is the image acquired by the real object.

Description

Image anti-counterfeiting identification method, device, equipment and computer readable storage medium

Technical Field

The application relates to the field of identification, in particular to an anti-counterfeiting identification method, an anti-counterfeiting identification device, anti-counterfeiting identification equipment and a computer readable storage medium for an image.

Background

In the information age, the biometric technology has been widely applied to various fields relating to identity authentication, such as access control, gate machines, user terminals, and the like, so as to realize the automatic authentication of user identity and achieve the purpose of guaranteeing automatic management, personal safety or information safety. Use the fingerprint identification technique of a big representative in the biological identification technique as an example, in current fingerprint identification technique, accessible fingerprint identification module response and gather the fingerprint. In practical application, the biological identification technology brings convenience, meanwhile, the problem of identity authentication through prosthesis deception exists, safety risks are brought to people, property and sensitive data, and how to prevent prosthesis deception is an important ring in the biological identification technology.

The existing biological identification anti-counterfeiting schemes can be mainly divided into three categories: material identification, dynamic identification, and structural identification. 1. Material identification, for example, a method for identifying a living body based on a binocular camera disclosed in publication No. CN107169405B (application No. 201710160685.X), which can determine whether an object providing a face is a living body by combining characteristics of materials reflecting different light intensities at the same distance by different materials; 2. dynamic authentication, for example, a living body recognition method disclosed in application publication No. CN110674680A (application No. 201910741203.9), which can combine static image face recognition and dynamic video motion recognition (e.g., blinking, turning around), and double-check to identify whether a face is a living body; structure identification, for example, a novel method for automatic fingerprint anti-counterfeiting and liveness detection disclosed in application publication No. CN108446633A (application No. 201810229464.8), which can acquire a fingerprint image with high-precision structural image content by an Optical Coherence Tomography (OCT) apparatus, and perform anti-counterfeiting fingerprint identification and liveness detection from the viewpoint of fingerprint structure.

In the research process of the prior related art, the inventor finds that in the aspect of fingerprint identification, dynamic identification is difficult to realize by fingerprint identification, anti-counterfeiting identification is mainly carried out by material identification, and if a fingerprint sleeve is manufactured by liquid glue commonly used in offices, a fingerprint identification module of a deception part is possible to pass through fingerprint verification. The office liquid glue is composed of colloid, water and electrolyte, when the liquid glue is not dried, the electrical characteristics of the liquid glue are similar to those of human skin tissues, and the liquid glue has transparent characteristics, so that the combination of a capacitance fingerprint sensor and an infrared detector can be deceived when a fingerprint sleeve made of the office liquid glue is worn on a real finger, and the material with the colloid, the water and the electrolyte can adjust the formula to enable the mechanical characteristics of the prepared fingerprint sleeve to be close to those of the human skin tissues, so that the ultrasonic fingerprint sensor can be further deceived. Therefore, the material can deceive three sensors of electricity, light and sound at the same time, and the traditional 'living fingerprint identification' technology based on material identification is invalid. However, when the OCT device is used for fingerprint verification, the actual product cannot be seen due to the problems of high cost and difficulty in landing the product, so that under the condition of limited anti-counterfeiting precision, how to prevent the fingerprint sleeve made of materials such as liquid glue and the like with colloid, water and electrolyte becomes a big problem in the current fingerprint identification research work.

Disclosure of Invention

The application provides an anti-counterfeiting identification method, an anti-counterfeiting identification device, an anti-counterfeiting identification equipment and a computer readable storage medium for determining whether a two-dimensional image of a target object is an image acquired by a real object by combining a three-dimensional image, and can solve the problem that a fingerprint cover made of materials such as liquid glue and the like with colloid, water and electrolyte has higher deception in the aspect of fingerprint identification in the prior art.

The application provides an anti-counterfeiting identification method and device of an image and a computer readable storage medium, which are used for determining whether a two-dimensional image of a collected target object is an image collected by a real object or not by combining a three-dimensional image, and can overcome the problem that a fingerprint cover made of materials such as liquid glue and the like with colloid, water and electrolyte has higher deception in the aspect of fingerprint identification in the prior art.

In a first aspect, the present application provides a method for anti-counterfeit identification of an image, the method comprising:

acquiring a two-dimensional image and a three-dimensional image of a target object;

detecting whether a preset three-dimensional image characteristic exists in the three-dimensional image, wherein the three-dimensional image characteristic is used for indicating the characteristic of the target object in the preset three-dimensional image;

and if so, determining that the two-dimensional image is the image acquired by the real object.

With reference to the first aspect of the present application, in a first possible implementation manner of the first aspect of the present application, the acquiring a three-dimensional image of a target object includes:

acquiring a plurality of two-dimensional tomographic images acquired from a target object by a two-dimensional camera under the shooting conditions of different shooting angles or different focal lengths;

and fusing the two-dimensional tomographic images to obtain a three-dimensional image.

With reference to the first possible implementation manner of the first aspect of the present application, in a second possible implementation manner of the first aspect of the present application, acquiring a plurality of two-dimensional tomographic images acquired from a target object under shooting conditions of different focal lengths by a two-dimensional camera includes:

and acquiring the position of a lens of the adjustable-focus macro camera adjusted by the voice coil motor so as to acquire a plurality of two-dimensional tomographic images acquired from the target object under the shooting conditions of different focal lengths.

With reference to the first aspect of the present application, in a third possible implementation manner of the first aspect of the present application, the three-dimensional image is a scanned image acquired by an OCT sensor, and the scanned image includes image features acquired from a target object under different depth-of-field conditions.

With reference to the first aspect of the present application, in a fourth possible implementation manner of the first aspect of the present application, the acquiring a two-dimensional image and a three-dimensional image of a target object includes:

and acquiring a two-dimensional image and a three-dimensional image acquired from the target object in the same preset acquisition region.

With reference to the first aspect of the present application, in a fifth possible implementation manner of the first aspect of the present application, it is determined that a three-dimensional image feature exists in a three-dimensional image when at least one of the following detection conditions is satisfied:

the three-dimensional image has image characteristics of a preset structure below the surface of the target object;

the three-dimensional image has continuous image characteristics which belong to the corresponding layered structure of the target object in the height Z-axis direction below the surface of the target object;

the image characteristics of the three-dimensional image projected onto the two-dimensional plane of the two-dimensional image are matched with the image characteristics of the two-dimensional image.

With reference to the first aspect of the present application or any one of the implementation manners of the first aspect of the present application, in a sixth possible implementation manner of the first aspect of the present application, the target object includes a target fingerprint object, a target iris object, a target human skin object, a target leather object, a target plant object, or a mineral object.

With reference to the sixth possible implementation manner of the first aspect of the present application, in a seventh possible implementation manner of the first aspect of the present application, before detecting whether a preset three-dimensional image feature exists in a three-dimensional image when a target object is a target fingerprint object or a target human skin object, the method further includes:

detecting whether a target object has preset living body characteristics or not;

and if so, triggering and detecting whether the three-dimensional image has three-dimensional image characteristics.

With reference to the seventh possible implementation manner of the first aspect of the present application, in an eighth possible implementation manner of the first aspect of the present application, the detecting whether the target object has the preset living body feature includes:

detecting whether the target object has pulse data in a preset pulse range and/or blood oxygen data in a preset blood oxygen range through an infrared-based pulse detector and/or an infrared-based blood oxygen detector;

and if so, determining that the living body characteristics exist in the target object.

In a second aspect, the present application provides an image anti-counterfeit device, comprising:

an acquisition unit configured to acquire a two-dimensional image and a three-dimensional image of a target object;

the detection unit is used for detecting whether a preset three-dimensional image characteristic exists in the three-dimensional image, wherein the three-dimensional image characteristic is used for indicating the characteristic of the target object in the preset three-dimensional image, and if the preset three-dimensional image characteristic exists, the determination unit is triggered;

and the determining unit is used for determining the two-dimensional image as the image acquired by the real object.

With reference to the second aspect of the present application, in a first possible implementation manner of the second aspect of the present application, the obtaining unit is specifically configured to:

With reference to the first possible implementation manner of the second aspect of the present application, in a second possible implementation manner of the second aspect of the present application, the obtaining unit is specifically configured to:

With reference to the second aspect of the present application, in a fourth possible implementation manner of the second aspect of the present application, the obtaining unit is specifically configured to:

With reference to the second aspect of the present application, in a fifth possible implementation manner of the second aspect of the present application, the detecting unit determines that the three-dimensional image has the three-dimensional image feature when at least one of the following detection conditions is satisfied:

With reference to the second aspect of the present application or any one of the implementation manners of the second aspect of the present application, in a sixth possible implementation manner of the second aspect of the present application, the target object comprises a target fingerprint object, a target iris object, a target human skin object, a target leather object, a target plant object or a mineral object.

With reference to the sixth possible implementation manner of the second aspect of the present application, in a seventh possible implementation manner of the second aspect of the present application, when the target object is a target fingerprint object or a target human skin object, the detecting unit is further configured to:

With reference to the seventh possible implementation manner of the second aspect of the present application, in an eighth possible implementation manner of the second aspect of the present application, the detecting unit is specifically configured to:

In a third aspect, the present application further provides an image anti-counterfeit identification device, which includes a processor and a memory, where the memory stores a computer program, and the processor executes the steps in any one of the methods provided in the embodiments of the present application when calling the computer program in the memory.

In a fourth aspect, the present application further provides a computer-readable storage medium storing a plurality of instructions, which are suitable for being loaded by a processor to perform the steps of any one of the methods provided by the embodiments of the present application.

From the above, the present application has the following advantageous effects:

in the anti-counterfeiting identification process of the image, on one hand, a two-dimensional image of a target object can be obtained, on the other hand, a three-dimensional image of the target object can be obtained, whether the three-dimensional image has a preset three-dimensional image characteristic or not is detected, the three-dimensional image characteristic is the characteristic of the target object in the preset three-dimensional image, and if the three-dimensional image characteristic exists, the two-dimensional image can be determined to be the image acquired by a real object, so that the fingerprint sleeve made of materials such as liquid glue with colloid, water and electrolyte can be combined with the three-dimensional image to judge whether the acquired fingerprint image is the real fingerprint image, and the problem that the fingerprint sleeve made of materials such as liquid glue with colloid, water and electrolyte has higher fingerprint identification performance in the prior art is solved;

secondly, the anti-counterfeiting identification of the two-dimensional image is carried out by combining the three-dimensional image, the counterfeiting cost is also greatly improved, the anti-counterfeiting technology is understood as a branch of the security technology, the attack cost is improved as the main technical purpose, and the three-dimensional image is introduced to realize the anti-counterfeiting identification of the two-dimensional image, which means that if the anti-counterfeiting identification is attempted to be deceived, the high counterfeiting cost required for counterfeiting the three-dimensional characteristic needs to be paid out, so the anti-counterfeiting grade and the security grade are greatly improved;

in addition, the anti-counterfeiting identification mode of the image can be further flexibly extended to anti-counterfeiting identification scenes of other images, the prejudice of anti-counterfeiting identification based on surface characteristics and the problem that related materials are easy to forge are avoided, and the anti-counterfeiting identification mode has high application value.

Drawings

In order to more clearly illustrate the technical solutions in the present application, the drawings that are required to be used in the present application will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without inventive effort.

FIG. 1 is a schematic view of a scene of an anti-counterfeit identification method for an image according to the present application;

FIG. 2 is a schematic flow chart of the anti-counterfeit identification method for the image of the present application;

FIG. 3 is a schematic flow chart of the present application for obtaining three-dimensional images;

FIG. 4 is a schematic view of a structure of an anti-counterfeit identification device according to the image of the present application;

fig. 5 is a schematic structural diagram of an anti-counterfeit identification device of the image of the present application.

Detailed Description

The technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings in the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In the description that follows, specific embodiments of the present application will be described with reference to steps and symbols executed by one or more computers, unless otherwise indicated. Accordingly, these steps and operations will be referred to, several times, as being performed by a computer, the computer performing operations involving a processing unit of the computer in electronic signals representing data in a structured form. This operation transforms the data or maintains it at locations in the computer's memory system, which may be reconfigured or otherwise altered in a manner well known to those skilled in the art. The data maintains a data structure that is a physical location of the memory that has particular characteristics defined by the data format. However, while the principles of the application have been described in language specific to above, it is not intended to be limited to the specific form set forth herein, and it will be recognized by those of ordinary skill in the art that various of the steps and operations described below may be implemented in hardware.

The principles of the present application may be employed in numerous other general-purpose or special-purpose computing, communication environments or configurations. Examples of well known computing systems, environments, and configurations that may be suitable for use with the application include, but are not limited to, hand-held telephones, personal computers, servers, multiprocessor systems, microcomputer-based systems, mainframe-based computers, and distributed computing environments that include any of the above systems or devices.

The terms "first", "second", and "third", etc. in this application are used to distinguish between different objects and not to describe a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions.

First, before the present application is introduced, the relevant contents of the present application with respect to the application background will be described.

The image anti-counterfeiting identification method, the image anti-counterfeiting identification device and the computer readable storage medium can be applied to image anti-counterfeiting identification equipment, are used for determining whether the acquired two-dimensional image of the target object is the image acquired by the real object by combining the three-dimensional image, and can solve the problem that a fingerprint sleeve made of materials such as liquid glue and the like with colloid, water and electrolyte has high deceptive performance in the aspect of fingerprint identification in the prior art.

In the present application, the target object may be not only a target fingerprint object but also a different object such as a target iris object, a target human skin object, a target leather object, a target plant object or a target mineral object.

The object having a three-dimensional feature referred to in the present application can be understood as an object having a specific three-dimensional feature not only on a surface but also below a surface.

For convenience of description, the present application introduces the anti-counterfeit identification method for an image, taking a target object as a target fingerprint object as an example.

The anti-counterfeiting identification Equipment for the image can be a server, a physical host or terminal Equipment, the terminal Equipment can be User Equipment (UE) such as a smart phone, a tablet Personal computer, a notebook computer, a palm computer, a desktop computer or a Personal Digital Assistant (PDA), or can be other Equipment which can be specifically adjusted along with an applied anti-counterfeiting identification scene, and is not limited herein.

Wherein, when the anti-fake identification method of image is used for the anti-fake identification scene of fingerprint image, specifically can be applied to the fingerprint identification module. The fingerprint identification module can be specifically configured in terminal equipment such as entrance guard, lock, smart mobile phone, panel computer, notebook computer, palm computer, desktop computer or PDA.

Wherein, the fingerprint identification module still can be divided into a plurality of equipment, carry out the fingerprint identification method that this application provided jointly, a scene sketch map of the fingerprint identification method of this application shown in fig. 1, in certain room that has the safety guarantee requirement, can dispose intelligent lock system 101, for example the computer lab of enterprise, intelligent lock system 101 can dispose the relevant sensor that can gather fingerprint image and also three-dimensional image in room door department, and upload the image of gathering to server 103 through network 102, confirm by server 103 in the high in the clouds whether the fingerprint image of gathering is real fingerprint image, confirm the state of opening and shutting of room door according to the result of confirming again.

The network 102 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, among others; the server 103 may be a server cluster including a plurality of servers, and the server 103 may also be a cloud server. There may be any number of networks 104 and servers 105, as desired.

The following description begins with the anti-counterfeit identification method for images provided by the present application.

First, referring to fig. 2, fig. 2 shows a schematic flow chart of the image anti-counterfeit identification method according to the present application, and the image anti-counterfeit identification method according to the present application may specifically include the following steps:

step S201, acquiring a two-dimensional image and a three-dimensional image of a target object;

step S202, detecting whether a preset three-dimensional image characteristic exists in the three-dimensional image, wherein the three-dimensional image characteristic is used for indicating the characteristic of the target object in the preset three-dimensional image, and if so, triggering step S203;

step S203, determining the two-dimensional image as an image acquired by the real object.

In the scheme shown in fig. 2, it can be seen that, in the process of image anti-counterfeiting identification, on one hand, a two-dimensional image of a target object can be obtained, on the other hand, a three-dimensional image of the target object can be obtained, and whether the three-dimensional image has a preset three-dimensional image characteristic is detected, if the three-dimensional image has the preset three-dimensional image characteristic, the two-dimensional image can be determined to be an image acquired by a real object, so that, for a fingerprint cover made of a material such as liquid glue with "colloid, water and electrolyte", the three-dimensional image can be combined to determine whether the obtained fingerprint image is a real fingerprint image, and the problem that the fingerprint cover made of the material such as liquid glue with "colloid, water and electrolyte" in the prior art has high deceptiveness in the aspect of fingerprint identification is solved;

The steps of the embodiment shown in FIG. 2 will now be described in detail.

In the present application, a two-dimensional image as well as a three-dimensional image of the target object may be acquired by an associated image sensor, for example, a two-dimensional form of a fingerprint image may be acquired by a fingerprint sensor, and a three-dimensional image of the finger on which the fingerprint is located may be acquired by a depth camera.

Taking a two-dimensional image as a fingerprint image in a fingerprint anti-counterfeiting identification scene as an example, acquiring a fingerprint image of a target fingerprint object, wherein the fingerprint image can be acquired in the current time period and can also be understood as a fingerprint image acquired in real time; alternatively, the fingerprint image may be a historical fingerprint image, which may be retrieved from another database or device storing fingerprint images, for example, to identify whether the historical fingerprint image is an authentic fingerprint image.

Certainly, in practical application, the image anti-counterfeiting identification method provided by the application is more suitable for judging and processing the real fingerprint image of the fingerprint image acquired by the fingerprint sensor in real time.

Taking an optical induction type sensor as an example, the fingerprint sensor can be an optical fingerprint sensor of a finger internal diffusion type, a trapezoidal prism type, a transparent optical self-luminous type and the like; taking an electrical sensing type sensor as an example, the fingerprint sensor may specifically be a glass-based capacitive sensor, such as a thin film transistor circuit and a cross-bus based electrical fingerprint sensor.

The capacitive fingerprint sensor can specifically include two implementation methods, one is a sensor structure of a high-density cross bus, which is equivalent to an orthogonal wire capacitive screen with a spacing of about 50 um; and secondly, a transparent fingerprint sensor array circuit is manufactured on a glass substrate by utilizing transparent devices such as metal oxide semiconductors and the like based on a Thin Film Transistor (TFT) process, and a transparent sheet capable of collecting fingerprint images in a capacitive mode is finally formed, so that the transparent capacitive fingerprint sensor is obtained.

Wherein, to fingerprint sensor's fingerprint detection area, can understand, fingerprint sensor disposes a contact surface usually, supplies the user to carry out pressing of finger, and fingerprint sensor rethread optical induction, electricity response, acoustics response etc. induction mode, the fingerprint characteristic of user's finger on the induction contact surface to adopt the fingerprint image that corresponds.

It should be understood that, in the present application, the fingerprint detection area of the fingerprint sensor does not necessarily refer to only the contact surface of the fingerprint sensor for the user to press the finger, but may also include a three-dimensional space area extending upward or toward the three-dimensional space, and thus, the three-dimensional image mentioned in the present application may also be acquired based on the fingerprint detection area of the fingerprint sensor.

Certainly, in some fingerprint sensors, the fingerprint characteristics of the user's finger may also be acquired "in the air", that is, the user's finger may face the fingerprint sensor and keep a certain distance, and the fingerprint sensor acquires the fingerprint characteristics of the user's finger through optical sensing and other ways to form a corresponding fingerprint image.

That is to say, the fingerprint detection region that this application is said can be understood as having the three-dimensional space region scope that can adjust along with actual need, but fingerprint image and three-dimensional image are gathered to this within range, promptly, this application can dispose the same collection region of predetermineeing, gathers two-dimensional image and three-dimensional image, and in practical application, this setting through the reduction, synchronized collection region, can further promote anti-fake identification precision.

In the application, after the fingerprint image acquired by the fingerprint sensor is acquired and the fingerprint information in the image is determined, the acquisition of the three-dimensional image is triggered, for example, after the on-site access control system detects that the fingerprint image is acquired by the fingerprint sensor, the acquisition of the three-dimensional image of the fingerprint detection area of the current fingerprint sensor is triggered.

Or, after the three-dimensional image meeting the requirement is acquired in the fingerprint detection area of the fingerprint sensor, triggering the fingerprint sensor to acquire the fingerprint image;

or, the two images do not need to be limited in time sequence, and the fingerprint image and the three-dimensional image are acquired in the same detection period.

That is, between the steps S201 and S202, there is no time sequence limitation, and the step S201 may be executed first, and then the step S202 may be executed; alternatively, step S202 may be executed first, and then step S201 may be executed; alternatively, step S201 and step S202 may be executed simultaneously, and the specific implementation is not limited herein.

The time for acquiring the three-dimensional image is similar to the above description for acquiring the fingerprint image, and details thereof are not repeated herein.

After the three-dimensional image is obtained, whether the three-dimensional image features preset in the application exist in the three-dimensional image can be detected, and the preset three-dimensional image features are features indicating real fingers in the preset three-dimensional image.

Illustratively, when a worker deploys the image anti-counterfeiting identification method provided by the application, the worker can acquire a large number of three-dimensional images in a fingerprint detection area in a real fingerprint identification scene of the fingerprint identification module, for example, manually press a contact surface of a fingerprint sensor, and extract and summarize features in the three-dimensional images in the real fingerprint identification scene, that is, preset three-dimensional image features.

Therefore, after the preset three-dimensional image characteristics exist in the current three-dimensional image, the fact that the three-dimensional image is acquired from a real fingerprint identification scene can be determined, namely, the previously acquired fingerprint image is an effective real fingerprint image, and the effect of judging whether the acquired fingerprint image is the real fingerprint image or not by combining the three-dimensional image is achieved.

Next, the three-dimensional image acquisition and the three-dimensional image feature determination processing according to the present application will be described in detail.

In an exemplary implementation, referring to a flowchart of acquiring a three-dimensional image according to the present application shown in fig. 3, acquiring a three-dimensional image of a target object according to the present application may specifically include the following steps:

step S301, acquiring a plurality of two-dimensional tomographic images acquired from a target object by a two-dimensional camera under the shooting conditions of different shooting angles or different focal lengths;

it is understood that light can penetrate certain structures, such as human soft tissue with certain finger thickness, and the longer the wavelength, the better the light penetration effect.

In the application, the image anti-counterfeiting recognition device can be configured with a two-dimensional camera, or a 2D camera, to obtain a two-dimensional tomographic image at the object focal plane of the target object for anti-counterfeiting recognition, where the two-dimensional tomographic image can be obtained by shooting from different shooting angles or different focal lengths, so that the two-dimensional tomographic image can be subsequently fused into a three-dimensional image with three-dimensional spatial information.

Correspondingly, in the application, the anti-counterfeiting identification equipment of the image can be specifically configured with the corresponding number of two-dimensional cameras according to the shooting condition requirements of the shooting angle or the focal length condition.

The camera can adjust the focal length in the shooting process, and two-dimensional tomographic images under different focal length conditions can be obtained by shooting object focal planes at different depths.

Further, in this application, this two-dimensional camera of adjustable focus specifically can be for the adjustable focus camera through voice coil motor focus regulation, and what correspond, two-dimensional tomographic image's acquisition processing includes:

If a plurality of focus-adjustable cameras are deployed, compared with a camera with an unadjustable focus, more two-dimensional tomographic images with different depths (or different focuses) can be obtained under the condition that the shooting angle is limited.

Step S302, a plurality of two-dimensional tomographic images are fused to obtain a three-dimensional image.

After two-dimensional tomographic images shot at different shooting angles or different focal lengths are obtained, image data can be processed and fused into a three-dimensional image with three-dimensional image information, the three-dimensional image can display the image information of a target object in a three-dimensional space from a three-dimensional space angle, and whether the two-dimensional image subjected to anti-counterfeiting recognition is an image acquired by a real object or not can be judged conveniently from the characteristics of the three-dimensional image.

It can be seen from the above that, in practical application, a three-dimensional image can be acquired by one or more two-dimensional cameras, and the types of the cameras, such as an adjustable focal length type and an unadjustable focal length type, can be adjusted according to actual needs, so as to meet the requirements of shooting conditions at different shooting angles and under different focal length conditions.

In addition, as another exemplary implementation manner of the present application, in practical applications, if there is a small-sized OCT sensor that can be applied to a terminal device, a scanned image acquired by using such an OCT sensor includes image features acquired from a target object under different depth of field conditions, that is, image information of the target object in a three-dimensional space, and therefore, the scanned image may also be used as a three-dimensional image mentioned in the present application for a subsequent application to determine whether a two-dimensional image of the target object is an image acquired by a real object from the three-dimensional image features.

Of course, in the present application, besides the two types of specific implementation manners described above, other types of specific implementation manners may also be adopted to acquire a three-dimensional image of the target object, and the specific implementation manner is not limited herein.

After the three-dimensional image is obtained, whether the three-dimensional image characteristics preset in the application exist in the image can be detected. Specifically, as another exemplary specific implementation manner of the present application, the detection condition for determining that the three-dimensional image has the preset three-dimensional image feature may be as follows:

1. the three-dimensional image has image characteristics of a preset structure below the surface of the target object;

it is understood that, in the present application, the target object is an object having a specific three-dimensional feature below the surface, and the three-dimensional feature corresponds to a preset structure of the target object below the surface, for example, in a fingerprint anti-counterfeit identification scenario, the subcutaneous tissue of the finger of the user has a "living" feature, such as a spectroscopic feature (e.g., muscle protein spectrum, hemoglobin spectrum), a dynamic feature (e.g., pulse, blood flow), a structural feature (e.g., subcutaneous hierarchical structure, capillary network), and the like, and therefore, the image feature presented by the feature at the image level can be configured as the image feature of the subcutaneous tissue (preset structure) referred to in the present application.

For another example, the iris has a basal layer structure and a pigment epithelium layer structure from front to back, the basal layer structure being rich in blood vessels and nerves; as another example, human skin is similar to fingers, much more so in the distinction of clarity; for another example, leather, or leather products, consist essentially of a layer of papillae and also of a network; for another example, the leaf of the plant mainly comprises the structures of the upper epidermis, the lower epidermis, the stomata, the closely arranged fence tissues, the sponge tissues with different sizes, the vascular bundle for carrying transportation tasks and the like, and the stem of the plant can comprise the structures of the periderm, the phloem, the vascular cambium, the xylem, the marrow and the like; also for example, various types of crystal structures characteristic of minerals.

Therefore, if the image characteristics of the preset structure exist in the three-dimensional image, the method can be used as a large basis for determining that the current three-dimensional image is obtained from the real object recognition scene.

2. The three-dimensional image has continuous image characteristics which belong to the corresponding layered structure of the target object in the height Z-axis direction below the surface of the target object;

it will be appreciated that the target object theoretically has a plurality of predetermined structures below its surface, and that the structures may constitute corresponding, continuous hierarchical structures, and therefore, in the present application, the hierarchical structures may also be configured as image features which are continuous in the direction of the Z-axis of height, referred to in the present application, and belong to the corresponding hierarchical structures of the target object.

The height Z-axis is a three-dimensional space of the detection area of the sensor, and corresponds to the Z-axis of X, Y, Z three coordinate axes. For example, the sensing contact surface of the fingerprint sensor is a plane formed by an X-axis and a Y-axis, and the Z-axis may be a direction perpendicular to the sensing contact surface of the fingerprint sensor. Of course, the specific direction of the height Z axis may be configured according to actual needs, and the direction may be used to indicate the height direction of the fingerprint detection area in the three-dimensional space on the basis of the fingerprint detection area of the fingerprint sensor.

Therefore, if the three-dimensional image has image features which are continuous in the height Z-axis direction and belong to the target object corresponding hierarchical structure, the determination that the current three-dimensional image is obtained from the real object recognition scene can be used as a big basis.

Of course, taking the counterfeit fingerprint identification scene of the fingerprint cover as an example, in practical application, if there is a fingerprint counterfeit means of the fingerprint cover to perform fingerprint identification, the finger wearing the fingerprint cover often presents a more obvious and abruptly changing layered structure characteristic in the three-dimensional image in the space where the fingerprint cover is located, at this time, compared with the layered structure image characteristic in the three-dimensional image acquired from the finger wearing the fingerprint cover, the continuous image characteristic belonging to the layered structure of the real skin in the height Z-axis direction has a more gently changing layered structure characteristic, so that the two can be accurately distinguished.

3. The image characteristics of the three-dimensional image projected onto the two-dimensional plane of the two-dimensional image are matched with the image characteristics of the two-dimensional image.

It will be appreciated that in an actual real object recognition scene, a three-dimensional image and a two-dimensional fingerprint image are captured from the same scene, and at a microscopic image level, both should have identical image features. Therefore, in the present application, the three-dimensional image and the two-dimensional image may be compared.

Specifically, the collected three-dimensional image may be projected from the three-dimensional space to a two-dimensional plane corresponding to the two-dimensional image, and then the image characteristics of the two images are compared to determine whether they match each other.

For example, if the two-dimensional image includes a projection image of a three-dimensional image and the images inside and outside the projection are continuous, it can be determined that the two images match each other.

For example, in the two-dimensional image projection part, the projected image in contact with the three-dimensional image on the projection plane may be determined to match the image characteristics of both.

Therefore, if the image characteristics of the three-dimensional image projected to the two-dimensional plane corresponding to the two-dimensional image are matched with the image characteristics of the two-dimensional image, the method can be used as a large basis for determining that the current three-dimensional image is obtained from a real object recognition scene.

The three detection methods described above may be understood as features of detecting, in addition to the continuity of the surface information, the relative position of the subsurface structure information of the surface information, the correspondence between the map of the subsurface structure information on the XY plane and the surface information of the corresponding region, the continuity of the subsurface structure information in the Z direction, and the depth of the subsurface structure information.

It can be seen that the three detection modes listed above can be applied alone to determine whether the current three-dimensional image is obtained from the real object recognition scene, and can also be applied in any combination, and when the selected detection conditions are all satisfied, it can be determined that the current three-dimensional image is obtained from the real object recognition scene.

The current three-dimensional image is determined to be obtained from the real object identification scene, which means that the two-dimensional image corresponding to the three-dimensional image is also obtained from the real object identification scene, namely, the two-dimensional image is the image collected for the real object, but not the forged fingerprint image formed by fingerprint forging means such as a fingerprint sleeve.

Further, in another exemplary implementation manner, for an object with living body properties such as a fingerprint or a human skin, in order to improve the effectiveness and accuracy of anti-counterfeiting identification, optical living body detection may be introduced before confirming whether a two-dimensional image is an image acquired by a real object through a three-dimensional image.

Correspondingly, before detecting whether the three-dimensional image has the preset three-dimensional image characteristics, the image anti-counterfeiting identification method provided by the application can further comprise the following steps:

and if so, triggering and detecting whether the three-dimensional image has the preset three-dimensional image characteristics.

It can be understood that the preset living characteristics are characteristics specific to the real user or the real finger compared with other objects (non-living bodies or dead objects), such as characteristics of a fingerprint cover, a normal body temperature of a human body, a skin color of the human body, a pulse and the like which are difficult to exist in a silica gel artificial hand.

Therefore, after the fingerprint image is obtained, whether the fingerprint image is a forged fingerprint image can be judged according to whether the living characteristics exist, and if the living characteristics exist, whether the fingerprint image is a real fingerprint image is judged according to the three-dimensional image characteristics.

As another exemplary implementation manner, here, detecting whether the target object has the preset living body feature may specifically include:

It can be understood that, by using the sensitivity characteristic of infrared rays with specific wavelengths (for example, 660nm red light and 940nm infrared light) to the change of blood volume generated by blood microcirculation at the tail end of blood vessels under the skin of a human body, the change of the blood oxygen protein content in blood of fingertips caused by the beating of the heart is detected, and after signal amplification, adjustment and other circuit processing, pulse signals synchronized with the pulse beating can be output, so that the pulse rate is calculated, and complete pulse wave waveform signals reflecting the blood volume change of the fingertips can also be output, and similarly, the blood oxygen saturation can also be calculated through the characteristic of the infrared rays. Based on this principle, a corresponding pulse detector and blood oxygen detector may be configured.

The fingerprint identification module that this application provided then can combine as the pulse that real human body has and/or blood oxygen scope after configuration pulse detector and/or blood oxygen detector, and the configuration is corresponding predetermines pulse scope and/or predetermines blood oxygen scope.

Therefore, when the measured pulse data is within the preset pulse range and/or when the measured blood oxygen data is within the preset blood oxygen range, the existence of the living body characteristic can be determined, and whether the fingerprint image is a real fingerprint image or not can be judged continuously from the three-dimensional image characteristic.

After confirming that the fingerprint image is real fingerprint image, the fingerprint identification module then can confirm that the fingerprint verification passes through, can trigger corresponding operations such as unblock.

In order to better implement the anti-counterfeiting identification method of the image, the application also provides an anti-counterfeiting identification device of the image.

Referring to fig. 4, fig. 4 is a schematic structural diagram of an image anti-counterfeit device according to the present application, in which the image anti-counterfeit device 400 may specifically include the following structure:

an acquisition unit 401 configured to acquire a two-dimensional image and a three-dimensional image of a target object;

the detection unit 402 is configured to detect whether a preset three-dimensional image feature exists in the three-dimensional image, where the three-dimensional image feature is used to indicate a feature of the target object in the preset three-dimensional image, and if the preset three-dimensional image feature exists, the determination unit is triggered;

a determining unit 403, configured to determine that the two-dimensional image is an image acquired by a real object.

In an exemplary implementation manner, the obtaining unit 401 is specifically configured to:

In another exemplary implementation manner, the obtaining unit 401 is specifically configured to:

In yet another exemplary implementation, the three-dimensional image is a scanned image acquired by the OCT sensor, and the scanned image includes image features acquired from the target object under different depth of field conditions.

In still another exemplary implementation, the detecting unit 402 determines that the three-dimensional image has the three-dimensional image feature when at least one of the following detection conditions is satisfied:

In yet another exemplary implementation, the target object includes a target fingerprint object, a target iris object, a target human skin object, a target leather object, a target plant object, or a mineral object.

In yet another exemplary implementation, when the target object is a target fingerprint object or a target human skin object, the detecting unit 402 is further configured to:

In another exemplary implementation manner, the detecting unit 402 is specifically configured to:

Referring to fig. 5, fig. 5 shows a schematic structural diagram of the image anti-counterfeiting identification device of the present application, specifically, the image anti-counterfeiting identification device of the present application includes a processor 501, a memory 502, and an input/output device 503, where when the processor 501 is used to execute a computer program stored in the memory 502, each step of the image anti-counterfeiting identification method in any embodiment corresponding to fig. 1 to 3 is implemented, and the memory 502 is used to store a computer program required by the processor 501 to execute the image anti-counterfeiting identification method in any embodiment corresponding to fig. 1 to 3.

Illustratively, a computer program may be partitioned into one or more modules/units, which are stored in memory 502 and executed by processor 501 to accomplish the present application. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of a computer program in a computer device.

The image anti-counterfeiting identification device can include, but is not limited to, a processor 501, a memory 502, and an input-output device 503. It will be understood by those skilled in the art that the illustration is merely an example of the image anti-counterfeiting identification device, and does not constitute a limitation on the image anti-counterfeiting identification device, and may include more or less components than those shown, or some components may be combined, or different components, for example, the image anti-counterfeiting identification device may further include a bus or the like, and the processor 501, the memory 502, the input and output device 503, and the like are connected via the bus.

The Processor 501 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor is the control center of the image anti-counterfeiting identification device, and various interfaces and lines are used to connect the various parts of the whole device.

The memory 502 may be used to store computer programs and/or modules, and the processor 501 may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory 502, as well as invoking data stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created from use of the anti-counterfeit recognition apparatus for the image, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

The processor 501, when executing the computer program stored in the memory 502, may specifically implement the following functions:

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the anti-counterfeiting identification device, the apparatus and the corresponding units of the image described above may refer to the descriptions of the anti-counterfeiting identification method of the image in any embodiment corresponding to fig. 1 to fig. 3, and are not described herein again in detail.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.

Therefore, the present application further provides a computer-readable storage medium, where a plurality of instructions are stored, where the instructions can be loaded by a processor to execute steps in the image anti-counterfeit recognition method in any embodiment corresponding to fig. 1 to fig. 3 in the present application, and specific operations may refer to descriptions of the image anti-counterfeit recognition method in any embodiment corresponding to fig. 1 to fig. 3, which are not described herein again.

Wherein the computer-readable storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.

Since the instructions stored in the computer-readable storage medium can execute the steps in the image anti-counterfeiting identification method in any embodiment corresponding to fig. 1 to 3, the beneficial effects that can be achieved by the image anti-counterfeiting identification method in any embodiment corresponding to fig. 1 to 3 can be achieved, which are described in detail in the foregoing description and are not repeated herein.

The method, the apparatus, the device and the computer-readable storage medium for image anti-counterfeit identification provided by the present application are introduced in detail, and a specific example is applied in the present application to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understanding the method and the core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A method for anti-counterfeit identification of an image, the method comprising:

detecting whether a preset three-dimensional image feature exists in the three-dimensional image, wherein the three-dimensional image feature is used for indicating the feature of the target object in the preset three-dimensional image;

and if so, determining that the two-dimensional image is an image acquired by a real object.

2. The method of claim 1, wherein the acquiring the three-dimensional image of the target object comprises:

acquiring a plurality of two-dimensional tomographic images acquired from the target object by a two-dimensional camera under the shooting conditions of different shooting angles or different focal lengths;

and fusing the two-dimensional tomographic images to obtain the three-dimensional image.

3. The method according to claim 2, wherein the acquiring a plurality of two-dimensional tomographic images acquired from the target object under the photographing conditions of different focal lengths by the two-dimensional camera comprises:

and acquiring the position of a lens of the adjustable-focus macro camera adjusted by the voice coil motor so as to acquire the plurality of two-dimensional tomographic images acquired from the target object under the shooting conditions of different focal lengths.

4. The method of claim 1, wherein the three-dimensional image is a scanned image acquired by an OCT sensor, the scanned image comprising image features acquired from the target object at different depths of field.

5. The method of claim 1, wherein the acquiring the two-dimensional image and the three-dimensional image of the target object comprises:

and acquiring the two-dimensional image and the three-dimensional image acquired from the target object in the same preset acquisition region.

6. The method according to claim 1, wherein the three-dimensional image is determined to have the three-dimensional image feature when at least one of the following detection conditions is satisfied:

and the image characteristics of the three-dimensional image projected to the two-dimensional plane of the two-dimensional image are matched with the image characteristics of the two-dimensional image.

7. The method of any one of claims 1 to 6, wherein the target object comprises a target fingerprint object, a target iris object, a target human skin object, a target leather object, a target plant object or a mineral object.

8. The method according to claim 7, wherein before the detecting whether the three-dimensional image has the preset three-dimensional image feature when the target object is the target fingerprint object or the target human skin object, the method further comprises:

detecting whether the target object has a preset living body characteristic or not;

and if so, triggering and detecting whether the three-dimensional image has the three-dimensional image characteristics.

9. The method according to claim 8, wherein the detecting whether the target object has the preset living body feature comprises:

if yes, determining that the living body characteristics exist in the target object.

10. An apparatus for anti-counterfeit identification of an image, the apparatus comprising:

the detection unit is used for detecting whether a preset three-dimensional image characteristic exists in the three-dimensional image, wherein the three-dimensional image characteristic is used for indicating the characteristic of the target object in the preset three-dimensional image, and if the preset three-dimensional image characteristic exists in the three-dimensional image, the determination unit is triggered;

and the determining unit is used for determining the two-dimensional image as an image acquired by a real object.

11. An apparatus for anti-counterfeit identification of an image, comprising a processor and a memory, the memory having stored therein a computer program, the processor executing the method according to any one of claims 1 to 9 when the processor calls the computer program in the memory.

12. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method of any of claims 1 to 9.