CN111104835A - Data verification method based on face recognition - Google Patents

Data verification method based on face recognition Download PDF

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Publication number
CN111104835A
CN111104835A CN201910013225.3A CN201910013225A CN111104835A CN 111104835 A CN111104835 A CN 111104835A CN 201910013225 A CN201910013225 A CN 201910013225A CN 111104835 A CN111104835 A CN 111104835A
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power consumption
image
field
data verification
equipment
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CN111104835B (en
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邓继红
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Zhejiang YdoolCom Technology Co ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172Classification, e.g. identification
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/0042Coin-freed apparatus for hiring articles; Coin-freed facilities or services for hiring of objects
    • G07F17/0057Coin-freed apparatus for hiring articles; Coin-freed facilities or services for hiring of objects for the hiring or rent of vehicles, e.g. cars, bicycles or wheelchairs

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
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Abstract

The invention relates to a data verification method based on face recognition, which comprises the step of operating a data verification system based on face recognition to carry out data verification, wherein the data verification system based on face recognition comprises position sensing equipment, field acquisition equipment, face analysis equipment, data verification equipment and the like. The data verification system based on the face recognition is safe, reliable and convenient to verify. Because the data verification equipment is introduced to compare the information obtained by field image analysis, and when the two are inconsistent, the identity suspicious signal is sent out, thereby being capable of giving an alarm in time.

Description

Data verification method based on face recognition
Technical Field
The invention relates to the field of face recognition, in particular to a data verification method based on face recognition.
Background
The human face recognition technology is based on a human face photograph or a human face image taken in real time, and is undoubtedly the most easily available. Because the face recognition technology uses the conventional general equipment, the price is within the acceptable range of the general users, and compared with other biological recognition technologies, the face recognition product has a high cost performance ratio.
In summary, the face recognition technology is a biological feature recognition technology which is high in precision, easy to use, high in stability, difficult to counterfeit and high in cost performance, and has extremely wide market application prospects.
Disclosure of Invention
According to an aspect of the present invention, there is provided a data verification method based on face recognition, the method including operating a data verification system based on face recognition to perform data verification, the data verification system based on face recognition including:
the position sensing equipment is arranged on a lock body of the shared bicycle and used for detecting the position of a lock tongue, sending a first control instruction when the lock tongue is positioned at a first position for completing locking, and sending a second control instruction when the lock tongue is positioned at a second position for completing unlocking;
the field acquisition equipment is connected with the position sensing equipment and used for acquiring the image of the environment where the shared bicycle is located when receiving a second control instruction so as to obtain a field environment image;
the face analysis equipment is connected with the field acquisition equipment and is used for analyzing the human face target with the shallowest depth of field in the field environment image so as to obtain corresponding identity information;
the data verification equipment is connected with the face analysis equipment and used for comparing the received identity information with the user information used for opening the sharing bicycle, and sending an identity suspicious signal when the identity information is inconsistent with the user information used for opening the sharing bicycle, otherwise, sending an identity valid signal;
the field acquisition equipment is also used for stopping image acquisition of the environment where the shared bicycle is located when the first control instruction is received;
the MMC storage equipment is connected with the system measuring equipment and the multi-equipment detecting equipment and is used for storing the power consumption of the system;
a system measurement device for analyzing a power consumption amount per unit time of a currently used battery based on historical power consumption data of the currently used battery to output as a system power consumption amount;
the multi-device detection device is respectively connected with the face analysis device, the data verification device and the field acquisition device, and is used for counting the power consumption of the face analysis device in unit time based on historical power consumption data of the face analysis device to serve as first power consumption, counting the power consumption of the data verification device in unit time based on historical power consumption data of the data verification device to serve as second power consumption, and counting the power consumption of the field acquisition device in unit time based on historical power consumption data of the field acquisition device to serve as third power consumption;
an available power adjusting device, connected to the system measurement device and the multi-device detection device, respectively, for determining an available power allocated to the face analysis device in a currently used remaining battery power based on a percentage of the first power consumption occupying the system power consumption, determining an available power allocated to the data verification device in a currently used remaining battery power based on a percentage of the second power consumption occupying the system power consumption, and determining an available power allocated to the field acquisition device in a currently used remaining battery power based on a percentage of the third power consumption occupying the system power consumption;
wherein, in the available power regulating device, the first power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the facial analysis device, the second power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the data verification device, and the third power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the field collection device;
wherein, the MMC memory device is also used for storing a first power consumption, a second power consumption and a third power consumption.
The invention has at least the following two important points:
(1) introducing data verification equipment to compare identity information obtained by field image analysis with user information used for opening a sharing bicycle, and sending an identity suspicious signal when the identity information and the user information are not consistent;
(2) and the available electric quantity of the equipment is adaptively adjusted based on the percentage of the equipment power consumption level occupying the system power consumption level so as to ensure the accuracy of the electric quantity distribution.
The data verification system based on the face recognition is safe, reliable and convenient to verify. Because the data verification equipment is introduced to compare the identity information obtained by field image analysis with the user information used for opening the sharing bicycle, and when the identity information and the user information are inconsistent, the identity suspicious signal is sent out, so that the phenomenon that the sharing bicycle is stolen can be alarmed in time.
Detailed Description
Embodiments of the present invention will be described in detail below.
The sharing of the single bicycle refers to that an enterprise provides bicycle sharing service in a campus, a subway station, a bus station, a residential area, a commercial area, a public service area and the like, and the sharing mode is a time-sharing rental mode. The shared bicycle is a novel environment-friendly and economical shared bicycle.
Shared bicycle is essentially a new type of vehicle rental business-bicycle rental business, which relies mainly on the carrier being a (bicycle) bicycle. The method can fully utilize the running cachexia of the bicycles caused by rapid economic development in the city, and maximally utilize the public road passing rate.
At present, in the design of an authentication mechanism of a shared bicycle, logic is too simple and is easy to crack, once cracking occurs, the shared bicycle can be illegally occupied by lawless persons, and data verification equipment cannot be introduced to compare identity information obtained by field image analysis with user information used for opening the shared bicycle, so that the safety performance of the shared bicycle cannot meet the existing requirements.
In order to overcome the defects, the invention builds a data verification method based on face recognition, the method comprises the step of operating a data verification system based on face recognition to carry out data verification, and the data verification system based on face recognition can effectively solve the corresponding technical problems.
The data verification system based on the face recognition shown according to the embodiment of the invention comprises:
the position sensing equipment is arranged on a lock body of the shared bicycle and used for detecting the position of a lock tongue, sending a first control instruction when the lock tongue is positioned at a first position for completing locking, and sending a second control instruction when the lock tongue is positioned at a second position for completing unlocking;
the field acquisition equipment is connected with the position sensing equipment and used for acquiring the image of the environment where the shared bicycle is located when receiving a second control instruction so as to obtain a field environment image;
the face analysis equipment is connected with the field acquisition equipment and is used for analyzing the human face target with the shallowest depth of field in the field environment image so as to obtain corresponding identity information;
the data verification equipment is connected with the face analysis equipment and used for comparing the received identity information with the user information used for opening the sharing bicycle, and sending an identity suspicious signal when the identity information is inconsistent with the user information used for opening the sharing bicycle, otherwise, sending an identity valid signal;
the field acquisition equipment is also used for stopping image acquisition of the environment where the shared bicycle is located when the first control instruction is received;
the MMC storage equipment is connected with the system measuring equipment and the multi-equipment detecting equipment and is used for storing the power consumption of the system;
a system measurement device for analyzing a power consumption amount per unit time of a currently used battery based on historical power consumption data of the currently used battery to output as a system power consumption amount;
the multi-device detection device is respectively connected with the face analysis device, the data verification device and the field acquisition device, and is used for counting the power consumption of the face analysis device in unit time based on historical power consumption data of the face analysis device to serve as first power consumption, counting the power consumption of the data verification device in unit time based on historical power consumption data of the data verification device to serve as second power consumption, and counting the power consumption of the field acquisition device in unit time based on historical power consumption data of the field acquisition device to serve as third power consumption;
an available power adjusting device, connected to the system measurement device and the multi-device detection device, respectively, for determining an available power allocated to the face analysis device in a currently used remaining battery power based on a percentage of the first power consumption occupying the system power consumption, determining an available power allocated to the data verification device in a currently used remaining battery power based on a percentage of the second power consumption occupying the system power consumption, and determining an available power allocated to the field acquisition device in a currently used remaining battery power based on a percentage of the third power consumption occupying the system power consumption;
wherein, in the available power regulating device, the first power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the facial analysis device, the second power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the data verification device, and the third power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the field collection device;
wherein, the MMC memory device is also used for storing a first power consumption, a second power consumption and a third power consumption.
Next, a detailed configuration of the data verification system based on face recognition according to the present invention will be further described.
In the data verification system based on face recognition:
the face analysis device is further connected with the position sensing device and used for entering a sleep mode when the first control instruction is received.
In the data verification system based on face recognition:
the data verification device is further connected with the position sensing device and used for entering a sleep mode when the first control instruction is received.
In the data verification system based on face recognition:
the face analysis device is further configured to enter an operating mode upon receiving the second control instruction.
In the data verification system based on face recognition:
the data verification device is further used for entering a working mode when the second control instruction is received.
In the data verification system based on face recognition, the method further comprises:
the recursive filtering device is connected with the field acquisition device and used for receiving the field environment image, performing recursive filtering processing based on noise amplitude on the field environment image to obtain a corresponding field filtering image, and outputting the field filtering image, wherein the performing recursive filtering processing based on noise amplitude on the field environment image comprises: the larger the noise amplitude of the live environment image is, the more the number of times of the recursive filtering processing performed on the live environment image is.
In the data verification system based on face recognition, the method further comprises:
a sharpness extraction device, connected to the recursive filtering device, configured to receive the live filtered image, perform a sharpness extraction operation on the live filtered image to obtain a corresponding live sharpness, and output the live sharpness, where performing the sharpness extraction operation on the live filtered image to obtain the corresponding live sharpness includes: and performing definition extraction operation on the field filtering image based on each pixel value of each pixel point of the field filtering image so as to obtain corresponding field definition.
In the data verification system based on face recognition, the method further comprises:
and the data judgment device is connected with the definition extraction device and used for receiving the field definition, sending a processing stopping command when the field definition exceeds a preset definition threshold value, and sending a continuous processing command when the field definition does not exceed the preset definition threshold value.
In the data verification system based on face recognition, the method further comprises:
and the cubic interpolation device is respectively connected with the face analysis device, the data judgment device and the definition extraction device, is used for executing image interpolation operation on the field filtering image by adopting a cubic interpolation method to obtain a cubic interpolation image and outputting the cubic interpolation image when receiving the continuous processing command, and is also used for directly taking the field filtering image as the cubic interpolation image and sending the cubic interpolation image to the face analysis device instead of the field environment image when receiving the processing stopping command.
In the data verification system based on face recognition, the method further comprises:
the PSTN communication interface is connected with the cubic interpolation equipment and used for receiving the cubic interpolation image and sending the cubic interpolation image through a PSTN communication link;
the recursive filtering device, the definition extracting device, the data judging device and the cubic interpolation device are respectively realized by SOC chips with different models;
wherein the recursive filtering device, the sharpness extracting device, the data judging device, and the cubic interpolating device share the same power supply input device.
In addition, pstn (public Switched Telephone network) defines: the PSTN provides an analog private channel, and the channels are connected through a plurality of telephone switches. When two hosts or router devices need to be connected through PSTN, a Modem (Modem) must be used on the network access side (i.e., the user loop side) at both ends to implement analog-to-digital, digital-to-analog conversion of signals. From the perspective of the OSI seven-layer model, the PSTN can be viewed as a simple extension of the physical layer, without providing services such as flow control, error control, etc. to the user. Furthermore, since the PSTN is a circuit-switched approach, a path is set up until released, and its full bandwidth can only be used by devices at both ends of the path, even though there is no data to transfer between them. Therefore, this circuit-switched approach does not achieve full utilization of network bandwidth. An example of internetworking over a PSTN is an example of internetworking that connects two local area networks over a PSTN. In the two local area networks, each router is provided with a serial port connected with a Modem, and the Modem is connected with a PSTN, thereby realizing the interconnection of the two local area networks.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.

Claims (10)

1. A data verification method based on face recognition, the method comprising operating a data verification system based on face recognition to perform data verification, the data verification system based on face recognition comprising:
the position sensing equipment is arranged on a lock body of the shared bicycle and used for detecting the position of a lock tongue, sending a first control instruction when the lock tongue is positioned at a first position for completing locking, and sending a second control instruction when the lock tongue is positioned at a second position for completing unlocking;
the field acquisition equipment is connected with the position sensing equipment and used for acquiring the image of the environment where the shared bicycle is located when receiving a second control instruction so as to obtain a field environment image;
the face analysis equipment is connected with the field acquisition equipment and is used for analyzing the human face target with the shallowest depth of field in the field environment image so as to obtain corresponding identity information;
the data verification equipment is connected with the face analysis equipment and used for comparing the received identity information with the user information used for opening the sharing bicycle, and sending an identity suspicious signal when the identity information is inconsistent with the user information used for opening the sharing bicycle, otherwise, sending an identity valid signal;
the field acquisition equipment is also used for stopping image acquisition of the environment where the shared bicycle is located when the first control instruction is received;
the MMC storage equipment is connected with the system measuring equipment and the multi-equipment detecting equipment and is used for storing the power consumption of the system;
a system measurement device for analyzing a power consumption amount per unit time of a currently used battery based on historical power consumption data of the currently used battery to output as a system power consumption amount;
the multi-device detection device is respectively connected with the face analysis device, the data verification device and the field acquisition device, and is used for counting the power consumption of the face analysis device in unit time based on historical power consumption data of the face analysis device to serve as first power consumption, counting the power consumption of the data verification device in unit time based on historical power consumption data of the data verification device to serve as second power consumption, and counting the power consumption of the field acquisition device in unit time based on historical power consumption data of the field acquisition device to serve as third power consumption;
an available power adjusting device, connected to the system measurement device and the multi-device detection device, respectively, for determining an available power allocated to the face analysis device in a currently used remaining battery power based on a percentage of the first power consumption occupying the system power consumption, determining an available power allocated to the data verification device in a currently used remaining battery power based on a percentage of the second power consumption occupying the system power consumption, and determining an available power allocated to the field acquisition device in a currently used remaining battery power based on a percentage of the third power consumption occupying the system power consumption;
wherein, in the available power regulating device, the first power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the facial analysis device, the second power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the data verification device, and the third power consumption accounts for a percentage of the system power consumption proportional to an available power allocated to the field collection device;
wherein, the MMC memory device is also used for storing a first power consumption, a second power consumption and a third power consumption.
2. The method of claim 1, wherein:
the face analysis device is further connected with the position sensing device and used for entering a sleep mode when the first control instruction is received.
3. The method of claim 2, wherein:
the data verification device is further connected with the position sensing device and used for entering a sleep mode when the first control instruction is received.
4. The method of claim 3, wherein:
the face analysis device is further configured to enter an operating mode upon receiving the second control instruction.
5. The method of claim 4, wherein:
the data verification device is further used for entering a working mode when the second control instruction is received.
6. The method of claim 5, wherein the system further comprises:
the recursive filtering device is connected with the field acquisition device and used for receiving the field environment image, performing recursive filtering processing based on noise amplitude on the field environment image to obtain a corresponding field filtering image, and outputting the field filtering image, wherein the performing recursive filtering processing based on noise amplitude on the field environment image comprises: the larger the noise amplitude of the live environment image is, the more the number of times of the recursive filtering processing performed on the live environment image is.
7. The method of claim 6, wherein the system further comprises:
a sharpness extraction device, connected to the recursive filtering device, configured to receive the live filtered image, perform a sharpness extraction operation on the live filtered image to obtain a corresponding live sharpness, and output the live sharpness, where performing the sharpness extraction operation on the live filtered image to obtain the corresponding live sharpness includes: and performing definition extraction operation on the field filtering image based on each pixel value of each pixel point of the field filtering image so as to obtain corresponding field definition.
8. The method of claim 7, wherein the system further comprises:
and the data judgment device is connected with the definition extraction device and used for receiving the field definition, sending a processing stopping command when the field definition exceeds a preset definition threshold value, and sending a continuous processing command when the field definition does not exceed the preset definition threshold value.
9. The method of claim 8, wherein the system further comprises:
and the cubic interpolation device is respectively connected with the face analysis device, the data judgment device and the definition extraction device, is used for executing image interpolation operation on the field filtering image by adopting a cubic interpolation method to obtain a cubic interpolation image and outputting the cubic interpolation image when receiving the continuous processing command, and is also used for directly taking the field filtering image as the cubic interpolation image and sending the cubic interpolation image to the face analysis device instead of the field environment image when receiving the processing stopping command.
10. The method of claim 9, wherein the system further comprises:
the PSTN communication interface is connected with the cubic interpolation equipment and used for receiving the cubic interpolation image and sending the cubic interpolation image through a PSTN communication link;
the recursive filtering device, the definition extracting device, the data judging device and the cubic interpolation device are respectively realized by SOC chips with different models;
wherein the recursive filtering device, the sharpness extracting device, the data judging device, and the cubic interpolating device share the same power supply input device.
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