CN106446827B - Iris recognition function detection method and device - Google Patents
Iris recognition function detection method and device Download PDFInfo
- Publication number
- CN106446827B CN106446827B CN201610839975.2A CN201610839975A CN106446827B CN 106446827 B CN106446827 B CN 106446827B CN 201610839975 A CN201610839975 A CN 201610839975A CN 106446827 B CN106446827 B CN 106446827B
- Authority
- CN
- China
- Prior art keywords
- terminal
- characteristic information
- iris recognition
- detected
- recognition function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims description 38
- 238000000034 method Methods 0.000 claims abstract description 26
- 230000006870 function Effects 0.000 claims description 104
- 230000002159 abnormal effect Effects 0.000 claims description 30
- 238000012545 processing Methods 0.000 claims description 20
- 238000011835 investigation Methods 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 12
- 238000004891 communication Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 9
- 238000012512 characterization method Methods 0.000 description 7
- 230000005856 abnormality Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 230000005236 sound signal Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000001133 acceleration Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/19—Sensors therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
Abstract
The present disclosure relates to a method and apparatus for detecting iris recognition function, the method comprising: acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal; comparing the first characteristic information with the second characteristic information to obtain a difference value; judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range, and if not, performing problem investigation on the terminal, thereby ensuring that a user can normally use the iris recognition function of the terminal and ensuring the quality of the terminal.
Description
Technical Field
The present disclosure relates to iris recognition technology, and in particular, to a method and apparatus for detecting iris recognition function.
Background
The iris recognition technology is based on the iris in eyes to carry out the identity recognition, and at present, the iris recognition technology has a larger application trend in terminal equipment such as mobile phones, computers and the like, and can help users to carry out the identity recognition.
Disclosure of Invention
In order to overcome the problems in the related art, the present disclosure provides a method and apparatus for detecting an iris recognition function.
According to a first aspect of an embodiment of the present disclosure, there is provided an iris recognition function detection method, including:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
and judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range.
In one embodiment, the determining whether the iris recognition function of the terminal to be detected is normal according to the difference value and a preset threshold range includes:
if the difference value does not exceed the preset threshold range, determining that the iris recognition function of the terminal to be detected is normal; or,
and if the difference value exceeds the preset threshold range, determining that the iris recognition function of the terminal to be detected is abnormal.
In one embodiment, the method further comprises:
if the iris recognition function of the terminal to be detected is abnormal, sending alarm information; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
In one embodiment, the acquiring the second characteristic information includes:
acquiring data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
and carrying out characterization processing on the data of the human eye model to acquire the second characteristic information.
In one embodiment, the method further comprises:
the second characteristic information is stored in a local memory.
According to a second aspect of the embodiments of the present disclosure, there is provided an iris recognition function detection apparatus including:
the acquisition module is configured to acquire the first characteristic information and the second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal;
the comparison module is configured to compare the first characteristic information with the second characteristic information to obtain a difference value;
and the judging module is configured to judge whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range.
In one embodiment, the determining module includes:
the first judging sub-module is configured to determine that the iris recognition function of the terminal to be detected is normal if the difference value does not exceed the preset threshold range; or,
and the second judging sub-module is used for determining that the iris recognition function of the terminal to be detected is abnormal if the difference value exceeds the preset threshold range.
In one embodiment, the apparatus further comprises:
the alarm module is configured to send alarm information if the iris recognition function of the terminal to be detected is abnormal; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
In one embodiment, the acquisition module includes:
the acquisition sub-module is configured to acquire the data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
and the processing sub-module is configured to perform characterization processing on the data of the human eye model so as to acquire the second characteristic information.
In one embodiment, the apparatus further comprises:
and a storage module configured to store the second characteristic information in a local memory.
According to a third aspect of the embodiments of the present disclosure, there is provided an iris recognition function detection apparatus including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
and judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
in one embodiment, first characteristic information and second characteristic information are acquired, the first characteristic information and the second characteristic information are compared, a difference value is acquired, whether the iris recognition function of the terminal to be detected is normal is judged according to the difference value and a preset threshold range, wherein the first characteristic information is information acquired according to the data of a human eye model acquired by the terminal to be detected, the second characteristic information is information acquired according to the data of a human eye model acquired by a standard sample terminal, the comparison is equivalent to the characteristic information acquired after the recognition of the human eye model by the terminal to be detected and the standard characteristic information, whether the iris recognition function of the terminal is normal is judged, if not normal, the terminal can be subjected to problem investigation, so that the iris recognition function of the terminal can be normally used by a user, and the quality of the terminal is ensured.
In one embodiment, a preset threshold range is predefined, if the difference value does not exceed the preset threshold range, it is determined that the iris recognition function of the terminal to be detected is normal, if the difference value exceeds the preset threshold range, it is determined that the iris recognition function of the terminal to be detected is abnormal, the iris recognition function of the terminal to be detected can be accurately detected, and the preset threshold range can be set and modified according to actual requirements, so that the method is flexible and convenient.
In one embodiment, when the iris recognition function of the terminal to be detected is abnormal, alarm information is sent, and the user is timely informed of the abnormality of the terminal to be detected, so that the user can conduct abnormality investigation on the terminal, and the abnormal terminal is prevented from entering a sales market.
In one embodiment, before the production line test, terminals capable of correctly realizing the iris recognition function are selected as standard sample terminals, the standard sample terminals are controlled to recognize the human eye model in the closed camera bellows, the data of the human eye model collected by each standard sample terminal are obtained, the data of the human eye model are subjected to characterization processing to obtain second characteristic information, the human eye model is recognized in the closed camera bellows, so that the influence of external infrared light on a detection result can be effectively prevented, the accuracy and the reliability of the detection result are ensured, and the second characteristic information is stored in a local memory.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram of an application scenario of an iris recognition function detection method according to an embodiment of the disclosure;
FIG. 2 is a flowchart illustrating a method of iris recognition function detection in accordance with an exemplary embodiment;
fig. 3 is a flowchart illustrating an iris recognition function detection method according to another exemplary embodiment;
fig. 4 is a block diagram showing an iris recognition function detection apparatus according to an exemplary embodiment;
fig. 5 is a block diagram showing an iris recognition function detection apparatus according to another exemplary embodiment;
fig. 6 is a block diagram showing an iris recognition function detection apparatus according to another exemplary embodiment;
fig. 7 is a block diagram showing an iris recognition function detection apparatus according to still another exemplary embodiment;
fig. 8 is a block diagram showing an iris recognition function detection apparatus according to still another exemplary embodiment;
fig. 9 is a block diagram illustrating an apparatus for iris recognition function detection according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
The iris recognition technology has a larger application trend in the field of mobile phones, and can help mobile phone users to carry out identity recognition. For terminals such as mobile phones and computers, the iris recognition function is realized through a plurality of functional modules, however, some problems occur in part of the iris recognition function of the terminals, so that the iris recognition function of the terminals cannot be normally used. The present disclosure provides an iris recognition function detection method, which detects an iris recognition function of a terminal to ensure that a user can normally use the iris recognition function.
Fig. 1 is a schematic application scenario diagram of an iris recognition function detection method according to an embodiment of the disclosure. As shown in fig. 1, in order to prevent external infrared light from affecting a detection result, the whole testing process is performed in a closed camera, in which a human eye model is directly in front of a terminal, generally, a distance between the human eye model and the terminal is about 20-50 cm, and a terminal position and a position of the human eye model are fixed, and the terminal can be a standard sample terminal or a terminal to be detected. For example, the mobile phone is connected with the computer through the USB interface, and the computer controls the mobile phone to collect iris image data.
Fig. 2 is a flowchart illustrating an iris recognition function detection method applied to a terminal or a server according to an exemplary embodiment, and as shown in fig. 2, the iris recognition function detection method includes the steps of:
in step S11, first feature information and second feature information are acquired; the first characteristic information is information obtained according to the data of the human eye model collected by the terminal to be detected, and the second characteristic information is information obtained according to the data of the human eye model collected by the standard sample terminal.
In this embodiment, in order to detect the iris recognition function of the terminal, some standard sample terminals may be determined first, where the standard sample terminals may accurately implement the iris recognition function, and first, the standard sample terminals identify the human eye model to obtain the data of the human eye model, and obtain second feature information according to the data of the human eye model, where the second feature information may be used as standard feature information to determine whether the feature information collected by other terminals to be detected is accurate. When other terminals are produced, the iris recognition function is required to be detected, and the terminal to be detected is controlled to recognize the human eye model so as to acquire the first characteristic information. The first characteristic information and the second characteristic information may be detailed characteristics of spots, filaments, crowns, stripes, recesses and the like of the iris.
In step S12, the first feature information is compared with the second feature information to obtain a difference value.
In this embodiment, the first feature information and the second feature information are compared to obtain a difference value between the first feature information and the second feature information, which is equivalent to comparing the feature information obtained from the terminal to be detected with the standard feature information, and obtaining the difference value between the two feature information and the standard feature information.
In step S13, whether the iris recognition function of the terminal to be detected is normal is determined according to the difference value and the preset threshold range.
In this embodiment, a preset threshold range (spec) may be set according to actual requirements, where the preset threshold is a range, and whether the iris recognition function of the terminal to be detected is normal may be determined according to the difference value and the preset threshold range. For example, if the preset threshold range is (-0.1 to 0.1), when the difference value is greater than or equal to-0.1 and less than or equal to 0.1, it is determined that the iris recognition function of the terminal is normal.
According to the iris recognition function detection method provided by the embodiment of the disclosure, the first characteristic information and the second characteristic information are acquired, the first characteristic information is compared with the second characteristic information, a difference value is acquired, whether the iris recognition function of the terminal to be detected is normal or not is judged according to the difference value and a preset threshold range, wherein the first characteristic information is acquired according to the data of the human eye model acquired by the terminal to be detected, the second characteristic information is acquired according to the data of the human eye model acquired by the standard sample terminal, the characteristic information acquired after the human eye model is recognized by the terminal to be detected is compared with the standard characteristic information, whether the iris recognition function of the terminal is normal or not is judged, if the iris recognition function of the terminal is abnormal, the problem can be checked on the abnormal terminal, so that the iris recognition function of the terminal can be normally used by a user, and the quality of the terminal is ensured.
Further, on the basis of the embodiment shown in fig. 2, the implementation of step S13 includes the following cases:
if the difference value does not exceed the preset threshold range, determining that the iris recognition function of the terminal to be detected is normal. Or if the difference value exceeds the preset threshold range, determining that the iris recognition function of the terminal to be detected is abnormal.
In this embodiment, the preset threshold range may be predefined, for example, the preset threshold range may be defined to be one thousandth, and if the difference value between the first feature information of the human eye model obtained from the terminal to be detected and the second feature information of the human eye model obtained from the standard sample terminal is within one thousandth, the iris recognition function of the terminal to be detected is determined to be normal, that is, if the difference value does not exceed the preset threshold range. If the difference value between the first characteristic information of the human eye model obtained from the terminal to be detected and the second characteristic information of the human eye model obtained from the standard sample terminal exceeds one thousandth, the terminal is unqualified, namely if the difference value exceeds a preset threshold range, the iris recognition function abnormality of the terminal to be detected is determined.
Optionally, the iris recognition function detection method may further include: if the iris recognition function of the terminal to be detected is abnormal, sending alarm information; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
In this embodiment, when it is determined that the iris recognition function of the terminal to be detected is abnormal, alarm information is sent, and the user is timely notified that the terminal to be detected is abnormal, so that the user can perform abnormality investigation for the terminal, and the abnormal terminal is prevented from entering the sales market. The alarm information can be text, picture, voice and other information types.
According to the iris recognition function detection method provided by the embodiment of the disclosure, a preset threshold range is predefined, if the difference value does not exceed the preset threshold range, the iris recognition function of the terminal to be detected is determined to be normal, if the difference value exceeds the preset threshold range, the iris recognition function of the terminal to be detected is determined to be abnormal, the iris recognition function of the terminal can be accurately detected, and the preset threshold range can be set and modified according to actual requirements, so that the iris recognition function detection method is flexible and convenient.
Fig. 3 is a flowchart showing an iris recognition function detection method according to another exemplary embodiment, which is applied to a terminal or a server, and on the basis of the above-described embodiment, as shown in fig. 3, the "step of acquiring second feature information" includes the steps of:
in step S21, data of a human eye model collected by the standard sample terminal in the closed camera bellows is obtained.
In this embodiment, before the production line test, terminals capable of correctly implementing the iris recognition function are selected as standard Sample (Golden Sample) terminals, the standard Sample terminals are controlled to recognize the human eye model in the closed camera bellows, and the data of the human eye model collected by each standard Sample terminal are obtained, where the data of the human eye model may be iris image data.
In step S22, the data of the human eye model is subjected to a characterization process to acquire second feature information.
In this embodiment, the data of the human eye model collected by each standard sample terminal is subjected to characterization processing, and the iris feature of the human eye model is extracted as the second feature information.
Optionally, after step S22, step S23 may be further included:
in step S23, the second characteristic information is stored in the local memory.
In this embodiment, after the second feature information is acquired, the second feature information may be stored, so as to be convenient for direct use in a subsequent detection process, and the local memory may be an embedded multimedia card (Embedded Multi Media Card, abbreviated as EMMC) or the like.
According to the iris function detection method provided by the embodiment of the disclosure, before production line testing, terminals capable of correctly realizing an iris recognition function are selected as standard sample terminals, the standard sample terminals are controlled to recognize a human eye model in a closed camera bellows, data of the human eye model collected by each standard sample terminal are obtained, the data of the human eye model are subjected to characterization processing to obtain second characteristic information, and the human eye model is recognized in the closed camera bellows, so that the influence of external infrared light on a detection result can be effectively prevented, the accuracy and the reliability of the detection result are ensured, and the second characteristic information is stored in a local memory.
Fig. 4 is a block diagram illustrating an iris recognition function detection apparatus according to an exemplary embodiment. As shown in fig. 4, the apparatus includes an acquisition module 11, a comparison module 12, and a judgment module 13.
The acquisition module 11 is configured to acquire first feature information and second feature information; the first characteristic information is information obtained according to the data of the human eye model collected by the terminal to be detected, and the second characteristic information is information obtained according to the data of the human eye model collected by the standard sample terminal.
The comparing module 12 is configured to compare the first feature information with the second feature information to obtain a difference value.
The judging module 13 is configured to judge whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and the preset threshold range.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Further, as shown in fig. 5 and 6, the judging module 13 includes a first judging sub-module 131 or a second judging sub-module 132.
The first judging sub-module 131 is configured to determine that the iris recognition function of the terminal to be detected is normal if the difference value does not exceed the preset threshold range.
The second judging sub-module 132 determines that the iris recognition function of the terminal to be detected is abnormal if the difference value exceeds the preset threshold range.
Optionally, as shown in fig. 6, the apparatus further comprises an alarm module 14.
The alarm module 14 is configured to send alarm information if the iris recognition function of the terminal to be detected is abnormal; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 7 is a block diagram showing an iris recognition function detection apparatus according to still another exemplary embodiment. As shown in fig. 7, the acquisition module 11 includes an acquisition sub-module 111 and a processing sub-module 112.
The acquisition sub-module 111 is configured to acquire data of a human eye model acquired by the standard sample terminal in the closed camera.
The processing sub-module 112 is configured to characterize the data of the human eye model to obtain second characteristic information.
Optionally, as shown in fig. 7, the apparatus further comprises a storage module 15.
The storage module 15 is configured to store the second characteristic information in the local memory.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 8 is a block diagram showing an iris recognition function detection apparatus according to still another exemplary embodiment. As shown in fig. 8, the apparatus includes a processor 21 and a memory 22:
a processor 21;
a memory 22 for storing instructions executable by the processor 21;
wherein the processor 21 is configured to:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
and judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and the preset threshold range.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 9 is a block diagram illustrating an apparatus for iris recognition function detection according to an exemplary embodiment. For example, apparatus 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.
Referring to fig. 8, apparatus 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the apparatus 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interactions between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phonebook data, messages, pictures, videos, and the like. The memory 804 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
The power component 806 provides power to the various components of the device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the device 800.
The multimedia component 808 includes a screen between the device 800 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. The front camera and/or the rear camera may receive external multimedia data when the device 800 is in an operational mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 further includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the apparatus 800. For example, the sensor assembly 814 may detect an on/off state of the device 800, a relative positioning of the components, such as a display and keypad of the apparatus 800, the sensor assembly 814 may also detect a change in position of the apparatus 800 or one component of the apparatus 800, the presence or absence of user contact with the apparatus 800, an orientation or acceleration/deceleration of the apparatus 800, and a change in temperature of the apparatus 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communication between the apparatus 800 and other devices, either in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi,2G or 3G, or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 804 including instructions executable by processor 820 of apparatus 800 to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
A non-transitory computer readable storage medium, which when executed by a processor of a mobile terminal, causes the mobile terminal to perform an iris recognition function detection method, the method comprising:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
and judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range.
The determining whether the iris recognition function of the terminal to be detected is normal according to the difference value and a preset threshold range includes:
if the difference value does not exceed the preset threshold range, determining that the iris recognition function of the terminal to be detected is normal; or,
and if the difference value exceeds the preset threshold range, determining that the iris recognition function of the terminal to be detected is abnormal.
Wherein the method further comprises:
if the iris recognition function of the terminal to be detected is abnormal, sending alarm information; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
Wherein the obtaining the second feature information includes:
acquiring data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
and carrying out characterization processing on the data of the human eye model to acquire the second characteristic information.
Wherein the method further comprises:
the second characteristic information is stored in a local memory.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (7)
1. An iris recognition function detection method, characterized by comprising:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal, wherein the terminal to be detected and the human eye model are in a closed camera bellows;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range;
the obtaining the second characteristic information includes:
acquiring data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
characterizing the data of the human eye model to obtain the second characteristic information;
the second characteristic information is stored in a local memory.
2. The method according to claim 1, wherein the determining whether the iris recognition function of the terminal to be detected is normal according to the difference value and a preset threshold range includes:
if the difference value does not exceed the preset threshold range, determining that the iris recognition function of the terminal to be detected is normal; or,
and if the difference value exceeds the preset threshold range, determining that the iris recognition function of the terminal to be detected is abnormal.
3. The method according to claim 2, wherein the method further comprises:
if the iris recognition function of the terminal to be detected is abnormal, sending alarm information; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
4. An iris recognition function detection apparatus, comprising:
the acquisition module is configured to acquire the first characteristic information and the second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal, wherein the terminal to be detected and the human eye model are in a closed camera bellows;
the comparison module is configured to compare the first characteristic information with the second characteristic information to obtain a difference value;
the judging module is configured to judge whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range;
the acquisition module comprises:
the acquisition sub-module is configured to acquire the data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
the processing sub-module is configured to perform characteristic processing on the data of the human eye model so as to acquire the second characteristic information;
and a storage module configured to store the second characteristic information in a local memory.
5. The apparatus of claim 4, wherein the determining module comprises:
the first judging sub-module is configured to determine that the iris recognition function of the terminal to be detected is normal if the difference value does not exceed the preset threshold range; or,
and the second judging sub-module is used for determining that the iris recognition function of the terminal to be detected is abnormal if the difference value exceeds the preset threshold range.
6. The apparatus of claim 5, wherein the apparatus further comprises:
the alarm module is configured to send alarm information if the iris recognition function of the terminal to be detected is abnormal; the alarm information comprises the identification of the terminal to be detected with the iris recognition function abnormal.
7. An iris recognition function detection apparatus, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
acquiring first characteristic information and second characteristic information; the first characteristic information is information acquired according to the data of the human eye model acquired by the terminal to be detected, and the second characteristic information is information acquired according to the data of the human eye model acquired by the standard sample terminal, wherein the terminal to be detected and the human eye model are in a closed camera bellows;
comparing the first characteristic information with the second characteristic information to obtain a difference value;
judging whether the iris recognition function of the terminal to be detected is normal or not according to the difference value and a preset threshold range;
the obtaining the second characteristic information includes:
acquiring data of the human eye model acquired by the standard sample terminal in the closed camera bellows;
characterizing the data of the human eye model to obtain the second characteristic information; the second characteristic information is stored in a local memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610839975.2A CN106446827B (en) | 2016-09-21 | 2016-09-21 | Iris recognition function detection method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610839975.2A CN106446827B (en) | 2016-09-21 | 2016-09-21 | Iris recognition function detection method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106446827A CN106446827A (en) | 2017-02-22 |
| CN106446827B true CN106446827B (en) | 2023-11-24 |
Family
ID=58166732
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610839975.2A Active CN106446827B (en) | 2016-09-21 | 2016-09-21 | Iris recognition function detection method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106446827B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108225740A (en) * | 2017-12-28 | 2018-06-29 | 浙江德景电子科技有限公司 | A kind of test method of terminal iris production |
| CN112583668A (en) * | 2020-12-10 | 2021-03-30 | 福州创实讯联信息技术有限公司 | Wireless link verification method and terminal |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105512532A (en) * | 2015-12-14 | 2016-04-20 | 惠州Tcl移动通信有限公司 | Mobile terminal screen control processing method and system based on iris recognition |
| EP3009960A1 (en) * | 2014-10-15 | 2016-04-20 | Samsung Electronics Co., Ltd. | User terminal apparatus and iris recognition method thereof |
| CN105704282A (en) * | 2016-03-23 | 2016-06-22 | 努比亚技术有限公司 | Detection method and apparatus for camera |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9164580B2 (en) * | 2012-08-24 | 2015-10-20 | Microsoft Technology Licensing, Llc | Calibration of eye tracking system |
-
2016
- 2016-09-21 CN CN201610839975.2A patent/CN106446827B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3009960A1 (en) * | 2014-10-15 | 2016-04-20 | Samsung Electronics Co., Ltd. | User terminal apparatus and iris recognition method thereof |
| CN105512532A (en) * | 2015-12-14 | 2016-04-20 | 惠州Tcl移动通信有限公司 | Mobile terminal screen control processing method and system based on iris recognition |
| CN105704282A (en) * | 2016-03-23 | 2016-06-22 | 努比亚技术有限公司 | Detection method and apparatus for camera |
Non-Patent Citations (1)
| Title |
|---|
| 基于虹膜识别技术的嵌入式信息采集系统的设计;孙弋等;《重庆邮电大学学报(自然科学版)》;20100815(第04期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106446827A (en) | 2017-02-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10452890B2 (en) | Fingerprint template input method, device and medium | |
| CN106951884B (en) | Fingerprint acquisition method and device and electronic equipment | |
| CN109446994B (en) | Gesture key point detection method and device, electronic equipment and storage medium | |
| US10216976B2 (en) | Method, device and medium for fingerprint identification | |
| CN107102772B (en) | Touch control method and device | |
| US10026293B2 (en) | Screen protection method and apparatus, and storage medium | |
| CN106802741B (en) | Method and device for determining screen edge touch event and mobile terminal | |
| CN108121631B (en) | Screen abnormal state reminding method and device | |
| EP3113071A1 (en) | Method and device for acquiring iris image | |
| US10083346B2 (en) | Method and apparatus for providing contact card | |
| CN107480785B (en) | Convolutional neural network training method and device | |
| KR20170038178A (en) | Method, apparatus, and mobile terminal for identificating fingerprint | |
| CN104243829A (en) | Self-shooting method and self-shooting device | |
| CN111200304A (en) | Temperature detection circuit, method and device of wireless charging coil and storage medium | |
| CN105208284A (en) | Photographing reminding method and device | |
| CN106446827B (en) | Iris recognition function detection method and device | |
| CN108647074B (en) | Method, device, hardware device and medium for displaying dynamic information in screen locking state | |
| CN107733021B (en) | Control method and device of electronic equipment | |
| CN108319899B (en) | Fingerprint identification method and device | |
| CN107402677B (en) | Method and device for recognizing finger lifting in touch operation and terminal | |
| US10671827B2 (en) | Method and device for fingerprint verification | |
| CN107273173B (en) | Fingerprint sensor control method and device and storage medium | |
| CN106919302B (en) | Operation control method and device of mobile terminal | |
| CN110708427B (en) | Information processing method, device and storage medium | |
| CN110213062B (en) | Method and device for processing message |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |