CN106650566A - Internet of things based road surface vehicle driving monitoring system - Google Patents
Internet of things based road surface vehicle driving monitoring system Download PDFInfo
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- CN106650566A CN106650566A CN201610785573.9A CN201610785573A CN106650566A CN 106650566 A CN106650566 A CN 106650566A CN 201610785573 A CN201610785573 A CN 201610785573A CN 106650566 A CN106650566 A CN 106650566A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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Abstract
The invention relates to an Internet of things based road surface vehicle driving monitoring system, which comprises a vehicle control device, an AVR32 chip, a high-definition camera and an image processing device, wherein the high-definition camera is arranged inside a road surface vehicle and used for photographing a driver so as to acquire a high-definition face image, the image processing device is used for performing image processing on the high-definition face image, and the AVR32 chip is connected with the vehicle control device and the image processing device and used for determining a control mode for the vehicle control device based on output of the image processing device. Legal driving of an authorized user for the road surface vehicle can be ensured according to the road surface vehicle driving monitoring system.
Description
Technical field
The present invention relates to field of vehicle control, more particularly to a kind of road vehicles traveling monitoring system based on Internet of Things.
Background technology
Vehicle is the general name of " car " and the unit " " of car.Car, refers to the vehicles that land wheel is rotated；,
From metering method of the ancient times to car.Car at that time is usually two wheels, therefore Che Yicheng claims one or two, just writes later
.As can be seen here, the literal sense of vehicle refers to and do not have in itself dynamic car, makes carriage, employment be people to draw or push away with Malaysia traction
Power car.With the development of science and technology, the automobile for having with steam engine to draw etc. again.
Although the species of vehicle is more, construct similar.This is standardized contribution, is also large-scale production stream
The needs of waterline.With development, the progress of science and technology and the change of demand of society, the profile of rolling stock has begun with change,
Especially passenger car is no longer whole-colored familiar faces.But their essential structure does not have great change, simply has
The parts of body have more scientific advanced structure design.In general, the essential structure of vehicle is by car body, body frame, traveling
The most of composition of portion, coupler and draft gear and brake apparatus five.
In prior art, the road vehicles of the road vehicles of traditional energy and the electronic energy become family expenses or public main flow
Vehicle, generally, the personnel that road vehicles are all recognized by car owner or car owner drive, but lawless person's hijacking vehicle also occurs
Situation occurs, therefore, it is desirable to which road vehicles itself differentiate to lawless person, and make the action that refusal continues to travel, so
The criminal offence of lawless person can be contained, it is to avoid traffic accident occurs, protect personal safety and the economic interests of car owner.
However, there is no such authentication scheme in prior art, accordingly, it would be desirable to a kind of new road vehicles monitoring side
Case, can introduce authentication scheme and unauthorized person is effectively differentiated.
The content of the invention
In order to solve the above problems, the invention provides a kind of road vehicles based on Internet of Things travel monitoring system, change
Road vehicles traveling monitoring system in prior art is made, human face detection tech is introduced and is introduced technology of Internet of things road pavement vehicle
Driver carries out identity discriminating, and is reacted in time when unauthorized user is found, is automatically stopped traveling behavior.
According to an aspect of the present invention, there is provided a kind of road vehicles based on Internet of Things travel monitoring system, the system
System includes vehicle control apparatus, AVR32 chips, high-definition camera and image processing equipment, high-definition camera, is arranged on road surface car
Inside, for being taken pictures to driver to obtain high definition face image, image processing equipment is used for high definition face image
Image procossing is carried out, AVR32 chips are connected respectively with vehicle control apparatus and image processing equipment, for setting based on image procossing
Standby output determines the control model to vehicle control apparatus.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things, including：Vehicle control apparatus,
Road pavement vehicle is controlled, for when validated user signal is received, safeguarding that the continuation of driver's road pavement vehicle drives,
It is additionally operable to, when disabled user's signal is received, according to surface conditions road vehicles pulling over observing be controlled；AVR32 chips, respectively
It is connected with the more sub- equipment of characteristic vector and vehicle control apparatus, for when recognition of face pass signal is received, sending conjunction
Method subscriber signal, is additionally operable to receiving recognition of face failure signal, sends disabled user's signal；High-definition camera, is arranged on
Inside road vehicles, for being taken pictures to obtain high definition face image to driver；Intensity compensation devices, with high-definition camera
Connection, for receiving high definition face image, based on the gray value of each pixel in high definition face image high definition face image is determined
Mean flow rate, and the mean flow rate of high definition face image and predetermined luminance are compared, it is average when high definition face image
Brightness is more than or equal to predetermined luminance, luminance-reduction is carried out to high definition face image and is adjusted to obtain brightness adjustment image, works as high definition
The mean flow rate of face image is less than predetermined luminance, luminance raising is carried out to high definition face image and is adjusted to obtain brightness adjustment figure
Picture；Gaussian smoothing equipment, is connected to receive brightness adjustment image with intensity compensation devices, Gauss is carried out to brightness adjustment image and is put down
It is sliding to process to obtain smoothed image；Gray processing processing equipment, is connected to receive smoothed image, and to smooth with Gaussian smoothing equipment
Image performs gray processing and processes to obtain gray level image；Histogram equalization equipment, is connected to receive with gray processing processing equipment
Gray level image, and histogram equalization process is performed to gray level image to obtain equilibrium figures picture；Feature extracting device, respectively with
Histogram equalization equipment and IP unpack equipment connection, and the equilibrium figures picture to receiving is processed；Feature extracting device includes ripple
Dynamic threshold value selects sub- equipment, the sub- equipment of processes pixel, the sub- equipment of matrix-split, the decimal system to change sub- equipment, characteristic vector acquisition
Sub- equipment and the more sub- equipment of characteristic vector；Fluctuation threshold selects sub- equipment to be connected with histogram equalization equipment, for calculating
The complexity of weighing apparatus image, the complexity based on equilibrium figures picture selects fluctuation threshold size, and the complexity of equilibrium figures picture is higher, selects
Fluctuation threshold it is bigger, fluctuation threshold is positive number；The sub- equipment of processes pixel selects sub- equipment and histogram with fluctuation threshold respectively
Balancing equipment connects, and for receiving equilibrium figures picture, following place is performed as object pixel for each pixel of equilibrium figures picture
Reason：The pixel centered on object pixel, obtains the object pixel matrix of 3 × 3 sizes, by object pixel matrix in equilibrium figures picture
Interior each pixel in addition to object pixel is compared as reference pixel with object pixel, to obtain binaryzation square
Battle array, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is made up of 8 binaryzation pixels, and reference pixel is more than or equal to subject image
Element and fluctuation threshold sum, then the pixel value of the corresponding binaryzation pixel of reference pixel is 1, and reference pixel subtracts less than object pixel
The difference gone after fluctuation threshold, then the pixel value of the corresponding binaryzation pixel of reference pixel be ﹣ 1, the reference pixel of other values
The pixel value of corresponding binaryzation pixel is 0；The sub- equipment of matrix-split is connected with the sub- equipment of processes pixel, for each is right
As the corresponding binaryzation matrix conversion of pixel is into a positive binaryzation matrix and a negative binaryzation matrix, positive binaryzation matrix by
8 binaryzation pixel values composition, negative binaryzation matrix is also made up of 8 binaryzation pixel values, positive binaryzation matrix each
Binaryzation pixel value deducts the binaryzation pixel value of negative binaryzation matrix relevant position, and can to obtain correspondence binaryzation matrix corresponding
The pixel value of the binaryzation pixel of position；The decimal system is changed sub- equipment and is connected with the sub- equipment of matrix-split, for each is right
As all binaryzation pixel values of the corresponding positive binaryzation matrix of pixel press its position in positive binaryzation matrix with first left back
Right order first up and then down again constitutes a binary number as the positive binary number of target, then the positive binary number of target is changed into
Decimal number is as the positive decimal number of target, to be additionally operable to all the two of the corresponding negative binaryzation matrix of each object pixel
Value pixel value constitutes a binary system by its position in negative binaryzation matrix with first left and then right order first up and then down again
Number changes into decimal number using as the negative decimal number of target as target negative binary number, then by target negative binary number；It is special
Levy vector and obtain sub- equipment and change sub- equipment with histogram equalization equipment and the decimal system respectively and be connected, for will be in equilibrium figures picture often
The pixel value of one object pixel is substituted for the corresponding positive goal decimal number of the object pixel and according to object pixel in equilibrium
The corresponding positive goal decimal number of all object pixels is constituted positive one-dimensional characteristic vector by the position in image, special as positive goal
Vectorial output is levied, is additionally operable to for the pixel value of each object pixel in equilibrium figures picture to be substituted for the corresponding negative mesh of the object pixel
Mark decimal number and according to position of the object pixel in equilibrium figures picture by the corresponding negative target decimal number of all object pixels
Composition negative one dimensional feature vector, as the output of negative target feature vector；The more sub- equipment of characteristic vector is obtained respectively with characteristic vector
Take sub- equipment and IP and unpack equipment connection, for positive goal characteristic vector to be carried out respectively with the positive characteristic vector of each benchmark
Match somebody with somebody, negative target feature vector is matched respectively with each benchmark negative feature vector, all the match is successful and matches for the two
The corresponding authorized user's title of the positive characteristic vector of benchmark authorized user's title phase corresponding with the benchmark negative feature vector for matching
Meanwhile, then recognition of face pass signal and authorized user's title corresponding with the positive characteristic vector of the benchmark for matching are exported, it is no
Then will output recognition of face failure signal；IP unpacks equipment, for being connected with long-range data server network, is connect by network
The IP packets at data server are received, and IP packets are unpacked to obtain 6LowPAN packets；Wherein, IP data
Bag is that 6LowPAN packets are carried out to beat the packet obtained after IP bags, and the load in 6LowPAN packets takes including data
The positive characteristic vector of each benchmark and each benchmark negative feature vector at business device, the head in 6LowPAN packets is compression number
According to the head in 6LowPAN packets after decompression is used to parse the load in 6LowPAN packets；Wherein, it is each
The positive characteristic vector of individual benchmark is that corresponding authorized user's benchmark face-image is carried out in advance and feature extracting device same operation
Positive characteristic vector pickup and the vector that obtains, each benchmark negative feature vector is pre- to corresponding authorized user's benchmark face-image
First carry out the vector for extracting and obtaining with the negative feature vector of feature extracting device same operation；Edge sensing equipment, with IP solutions
Bag equipment connects, and for receiving the 6LowPAN packets that IP unpacks equipment output, acquisition is rendered as the 6LowPAN of compressed data
The head of packet, decompresses with the head in the 6LowPAN packets after being decompressed to the head of 6LowPAN packets；
6LowPAN unpacks equipment, is connected with edge sensing equipment, in receiving 6LowPAN packets to obtain 6LowPAN packets
Load, and the load in 6LowPAN packets is parsed based on the head in the 6LowPAN packets after decompression, with
Obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector；Wherein, alternatively, replace high using wavelet filtering equipment
This smoothing arrangement, wavelet filtering equipment is connected to receive brightness adjustment image with intensity compensation devices, and brightness adjustment image is entered
Row wavelet filtering processes to obtain smoothed image.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things：High-definition camera also includes dodging
Light lamp controller and flash lamp.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things：High-definition camera also includes bright
Degree sensor, for detecting real time environment brightness.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real
When ambient brightness control flash lamp opening and closing.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real
When ambient brightness control flash lamp opening and closing include：When real time environment brightness is more than predetermined luminance threshold value, flash lamp is closed.
More specifically, in the road vehicles traveling monitoring system based on Internet of Things：Photoflash controller is based on real
When ambient brightness control flash lamp opening and closing include：When real time environment brightness is less than or equal to predetermined luminance threshold value, flash of light is opened
Lamp and according to the flash luminance of real time environment brightness adjustment flash lamp, real time environment brightness is lower, and the flash luminance of flash lamp is got over
It is high.
Description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the structure side that the road vehicles based on Internet of Things according to embodiment of the present invention travel monitoring system
Block diagram.
Reference：1 vehicle control apparatus；2AVR32 chips；3 high-definition cameras；4 image processing equipments
Specific embodiment
The embodiment that the road vehicles based on Internet of Things of the present invention travel monitoring system is entered below with reference to accompanying drawings
Row is described in detail.
Currently, road vehicles traveling monitoring system lacks the safe access control equipment differentiated to driver identity,
Cause the security performance of road vehicles not high, it is easy to carry out criminal offence to lawless person's hijacking vehicle and bring convenience, so as to
Infringement is produced in personal safety and economic interests to car owner.
In order to overcome above-mentioned deficiency, the present invention to build a kind of road vehicles based on Internet of Things and travelled monitoring system, profit
Monitoring system is travelled with existing road vehicles, it is transformed to increase face recognition device and network communication equipment, it is complete
The accurate discriminating of road vehicles driver identity in pairs.
Fig. 1 is the structure side that the road vehicles based on Internet of Things according to embodiment of the present invention travel monitoring system
Block diagram, the system include vehicle control apparatus, AVR32 chips, high-definition camera and image processing equipment, high-definition camera,
It is arranged on inside road vehicles, for being taken pictures to driver to obtain high definition face image, it is right that image processing equipment is used for
High definition face image carries out image procossing, and AVR32 chips are connected respectively with vehicle control apparatus and image processing equipment, for base
Determine the control model to vehicle control apparatus in the output of image processing equipment.
Then, the concrete structure for continuing to travel the road vehicles based on Internet of Things of the present invention monitoring system enters traveling one
The explanation of step.
The system includes：Vehicle control apparatus, road pavement vehicle is controlled, for receiving validated user signal
When, the continuation for safeguarding driver's road pavement vehicle drives, and is additionally operable to when disabled user's signal is received, according to surface conditions control
Road vehicles pulling over observing processed.
The system includes：AVR32 chips, are connected respectively with the more sub- equipment of characteristic vector and vehicle control apparatus, use
In when recognition of face pass signal is received, validated user signal is sent, is additionally operable to receiving recognition of face failure signal,
Send disabled user's signal；High-definition camera, is arranged on inside road vehicles, for being taken pictures to obtain high definition to driver
Face image.
The system includes：Intensity compensation devices, are connected with high-definition camera, for receiving high definition face image, are based on
The gray value of each pixel determines the mean flow rate of high definition face image, and putting down high definition face image in high definition face image
Brightness is compared with predetermined luminance, when the mean flow rate of high definition face image is more than or equal to predetermined luminance, to high definition face
Image carries out luminance-reduction and adjusts to obtain brightness adjustment image, when the mean flow rate of high definition face image is less than predetermined luminance,
Carry out luminance raising to high definition face image to adjust to obtain brightness adjustment image.
The system includes：Gaussian smoothing equipment, is connected to receive brightness adjustment image, to brightness with intensity compensation devices
Adjustment image carries out Gaussian smoothing to obtain smoothed image；Gray processing processing equipment, is connected to connect with Gaussian smoothing equipment
Smoothed image is received, and gray processing is performed to smoothed image and process to obtain gray level image.
The system includes：Histogram equalization equipment, is connected to receive gray level image with gray processing processing equipment, and right
Gray level image performs histogram equalization and processes to obtain equilibrium figures picture.
The system includes：Feature extracting device, unpacks equipment and is connected, to receiving with histogram equalization equipment and IP respectively
To equilibrium figures picture processed；Feature extracting device includes that fluctuation threshold selects sub- equipment, the sub- equipment of processes pixel, matrix to tear open
Molecular Devices, the decimal system change sub- equipment, characteristic vector and obtain sub- equipment and the more sub- equipment of characteristic vector；Fluctuation threshold is selected
Sub- equipment is connected with histogram equalization equipment, and for calculating the complexity of equilibrium figures picture, the complexity based on equilibrium figures picture is selected
Fluctuation threshold size, the complexity of equilibrium figures picture is higher, and the fluctuation threshold of selection is bigger, and fluctuation threshold is positive number；Processes pixel
Sub- equipment selects sub- equipment and histogram equalization equipment to be connected with fluctuation threshold respectively, for receiving equilibrium figures picture, for equilibrium
Each pixel of image performs following process as object pixel：The pixel centered on object pixel, obtains in equilibrium figures picture
The object pixel matrix of 3 × 3 sizes is taken, using each pixel in object pixel matrix in addition to object pixel as reference
Pixel is compared with object pixel, and to obtain binaryzation matrix, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is by 8
Binaryzation pixel is constituted, and reference pixel is more than or equal to object pixel and fluctuation threshold sum, then the corresponding binaryzation of reference pixel
The pixel value of pixel is 1, and reference pixel deducts the difference after fluctuation threshold less than object pixel, then the corresponding two-value of reference pixel
The pixel value for changing pixel is ﹣ 1, and the pixel value of the corresponding binaryzation pixel of reference pixel of other values is 0；Matrix-split sets
It is standby to be connected with the sub- equipment of processes pixel, for by the corresponding binaryzation matrix conversion of each object pixel into a positive binaryzation
Matrix and a negative binaryzation matrix, positive binaryzation matrix is made up of 8 binaryzation pixel values, bears binaryzation matrix also by 8
Binaryzation pixel value is constituted, and each binaryzation pixel value of positive binaryzation matrix deducts the two of negative binaryzation matrix relevant position
Value pixel value can obtain the pixel value of the binaryzation pixel of correspondence binaryzation matrix relevant position；The decimal system changes sub- equipment
It is connected with the sub- equipment of matrix-split, for by all binaryzation pixel values of the corresponding positive binaryzation matrix of each object pixel
One binary number is constituted as target using first left and then right order first up and then down again by its position in positive binaryzation matrix
Positive binary number, then the positive binary number of target is changed into into decimal number so that used as the positive decimal number of target, being additionally operable to will be each
All binaryzation pixel values of the corresponding negative binaryzation matrix of individual object pixel are by its position in negative binaryzation matrix with elder generation
Left back right side order first up and then down again constitutes a binary number as target negative binary number, then target negative binary number is turned
Chemical conversion decimal number is using as the negative decimal number of target；Characteristic vector obtains sub- equipment and enters with histogram equalization equipment and ten respectively
The sub- equipment connection of system conversion, it is corresponding for the pixel value of each object pixel in equilibrium figures picture to be substituted for into the object pixel
Positive goal decimal number simultaneously enters the corresponding positive goal ten of all object pixels according to position of the object pixel in equilibrium figures picture
Array processed, as the output of positive goal characteristic vector, is additionally operable to each subject image in equilibrium figures picture into positive one-dimensional characteristic vector
The pixel value of element is substituted for the corresponding negative target decimal number of the object pixel and the position according to object pixel in equilibrium figures picture
Put and the corresponding negative target decimal number of all object pixels is constituted into negative one dimensional feature vector, it is defeated as negative target feature vector
Go out；The more sub- equipment of characteristic vector obtains respectively sub- equipment with characteristic vector and IP unpacks equipment and is connected, for positive goal is special
Levy vector matched with the positive characteristic vector of each benchmark respectively, by negative target feature vector respectively with each benchmark negative feature to
Amount matched, the two all the match is successful and the corresponding authorized user's title of the positive characteristic vector of benchmark that matches with match
When the benchmark negative feature corresponding authorized user's title of vector is identical, then export recognition of face pass signal and with the base for matching
The corresponding authorized user's title of accurate positive characteristic vector, otherwise will output recognition of face failure signal.
The system includes：IP unpack equipment, for being connected with long-range data server network, by network reception come
IP packets from data server, and IP packets are unpacked to obtain 6LowPAN packets；Wherein, IP packets are
6LowPAN packets are carried out to beat the packet obtained after IP bags, the load in 6LowPAN packets includes data server
The positive characteristic vector of each benchmark at place and each benchmark negative feature vector, the head in 6LowPAN packets is compressed data, solution
The head in 6LowPAN packets after pressure is used to parse the load in 6LowPAN packets；Wherein, each base
Accurate positive characteristic vector is to carry out the positive spy with feature extracting device same operation in advance to corresponding authorized user's benchmark face-image
The vector that vector is extracted and obtained is levied, each benchmark negative feature vector is pre- advanced to corresponding authorized user's benchmark face-image
The vector that row is extracted and obtained with the negative feature vector of feature extracting device same operation.
The system includes：Edge sensing equipment, unpacks equipment and is connected with IP, and for receiving IP equipment output is unpacked
6LowPAN packets, acquisition is rendered as the head of the 6LowPAN packets of compressed data, the head solution to 6LowPAN packets
Pressure is with the head in the 6LowPAN packets after being decompressed.
The system includes：6LowPAN unpacks equipment, is connected with edge sensing equipment, for receiving 6LowPAN packets
Load in obtain 6LowPAN packets, and based on the head in the 6LowPAN packets after decompression to 6LowPAN data
Load in bag is parsed, to obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector.
Wherein, alternatively, Gaussian smoothing equipment is replaced using wavelet filtering equipment, wavelet filtering equipment sets with luminance compensation
Standby connection carries out wavelet filtering to brightness adjustment image and processes to obtain smoothed image to receive brightness adjustment image.
Alternatively, in the control platform：High-definition camera also includes photoflash controller and flash lamp；High-definition camera
Head also includes luminance sensor, for detecting real time environment brightness；Photoflash controller is glistened based on real time environment brilliance control
The opening and closing of lamp；Photoflash controller is included based on the opening and closing of real time environment brilliance control flash lamp：When real time environment brightness is more than
During predetermined luminance threshold value, flash lamp is closed；And opening and closing bag of the photoflash controller based on real time environment brilliance control flash lamp
Include：When real time environment brightness is less than or equal to predetermined luminance threshold value, opens flash lamp and glistened according to real time environment brightness adjustment
The flash luminance of lamp, real time environment brightness is lower, and the flash luminance of flash lamp is higher.
In addition, wave filter, as the term suggests, it is the device that ripple is filtered." ripple " is that a physics widely is general
Read, in electronic technology field, " ripple " is narrowly confined to refer in particular to the value for describing various physical quantitys with time fluctuations
Process.The effect that the process passes through various kinds of sensors, is converted into the function of time of voltage or electric current, referred to as various physical quantitys
Time waveform, or referred to as signal.Because the independent variable time is continuous value, referred to as continuous time signal,
Habitually it is referred to as analog signal again.
With digital electronic computer technology generation and develop rapidly, for the ease of computer to signal at
Reason, generates and continuous time signal is transformed into into the complete theoretical and method of discrete-time signal in the case where sampling theorem is instructed.
That is, sample value that can only with original analog signal on series of discrete time coordinate point is expressed primary signal and is not lost
Lose any information since these concepts expression of ripple, waveform, signal be various physical quantitys in objective world change, naturally
It is the carrier of the various information that modern society depends on for existence.Information needs to propagate, and what is leaned on is exactly the transmission of waveform signal.Signal exists
Its generation, conversion, each link of transmission distort because of the presence of environment and interference, even quite a lot of
In the case of, this distortion is also very serious, causes signal and its entrained information to be embedded in dearly in the middle of noise.In order to
These noises are filtered, recovers the signal of script, need to be filtered process using various wave filters.
Monitoring system is travelled using the road vehicles based on Internet of Things of the present invention, cannot be road surface car for prior art
Provide driver identity authentication scheme technical problem, by road vehicles travel monitoring system in integrated high-precision people
Face feature extraction matching unit and jumbo network communication equipment, find in time lawless person, and are braked rapidly, so as to
The security performance of road vehicles is improved on the whole.
Although it is understood that the present invention is disclosed as above with preferred embodiment, but above-described embodiment and being not used to
Limit the present invention.For any those of ordinary skill in the art, under without departing from technical solution of the present invention ambit,
All many possible variations and modification are made to technical solution of the present invention using the technology contents of the disclosure above, or be revised as
With the Equivalent embodiments of change.Therefore, every content without departing from technical solution of the present invention, according to the technical spirit pair of the present invention
Any simple modification made for any of the above embodiments, equivalent variations and modification, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (2)
1. a kind of road vehicles based on Internet of Things travel monitoring system, and the system includes vehicle control apparatus, AVR32 cores
Piece, high-definition camera and image processing equipment, high-definition camera is arranged on inside road vehicles, for clapping driver
According to obtain high definition face image, image processing equipment is used to carry out high definition face image image procossing, AVR32 chips difference
It is connected with vehicle control apparatus and image processing equipment, determines to vehicle control apparatus for the output based on image processing equipment
Control model.
2. the road vehicles based on Internet of Things as claimed in claim 1 travel monitoring system, it is characterised in that the system bag
Include：
Vehicle control apparatus, road pavement vehicle is controlled, for when validated user signal is received, safeguarding that driver satisfies the need
The continuation of face vehicle drives, and is additionally operable to, when disabled user's signal is received, control road vehicles according to surface conditions and keep to the side to stop
Car；
AVR32 chips, are connected respectively with the more sub- equipment of characteristic vector and vehicle control apparatus, for receiving recognition of face
During pass signal, validated user signal is sent, be additionally operable to receiving recognition of face failure signal, send disabled user's signal；
High-definition camera, is arranged on inside road vehicles, for being taken pictures to obtain high definition face image to driver；
Intensity compensation devices, are connected with high-definition camera, for receiving high definition face image, based in high definition face image each
The gray value of pixel determines the mean flow rate of high definition face image, and the mean flow rate of high definition face image and predetermined luminance are entered
Row compares, and when the mean flow rate of high definition face image is more than or equal to predetermined luminance, to high definition face image luminance-reduction tune is carried out
It is whole to obtain brightness adjustment image, when high definition face image mean flow rate be less than predetermined luminance, high definition face image is carried out
Luminance raising adjusts to obtain brightness adjustment image；
Gaussian smoothing equipment, is connected to receive brightness adjustment image with intensity compensation devices, and to brightness adjustment image Gauss is carried out
Smoothing processing is obtaining smoothed image；
Gray processing processing equipment, is connected to receive smoothed image with Gaussian smoothing equipment, and smoothed image is performed at gray processing
Manage to obtain gray level image；
Histogram equalization equipment, is connected to receive gray level image with gray processing processing equipment, and gray level image is performed straight
Square figure equilibrium treatment is obtaining equilibrium figures picture；
Feature extracting device, unpacks equipment and is connected with histogram equalization equipment and IP respectively, and the equilibrium figures picture to receiving is carried out
Process；Feature extracting device includes that fluctuation threshold selects sub- equipment, the sub- equipment of processes pixel, the sub- equipment of matrix-split, the decimal system
Change sub- equipment, characteristic vector and obtain sub- equipment and the more sub- equipment of characteristic vector；Fluctuation threshold selects sub- equipment and histogram
Balancing equipment connects, and for calculating the complexity of equilibrium figures picture, the complexity based on equilibrium figures picture selects fluctuation threshold size,
The complexity of weighing apparatus image is higher, and the fluctuation threshold of selection is bigger, and fluctuation threshold is positive number；The sub- equipment of processes pixel respectively with fluctuation
Threshold value selects sub- equipment and the connection of histogram equalization equipment, for receiving equilibrium figures picture, for each pixel of equilibrium figures picture
Following process is performed as object pixel：The pixel centered on object pixel, obtains the object of 3 × 3 sizes in equilibrium figures picture
Picture element matrix, each pixel in object pixel matrix in addition to object pixel is entered as reference pixel with object pixel
Row compares, and to obtain binaryzation matrix, binaryzation matrix is 3 × 3 sizes, and binaryzation matrix is made up of 8 binaryzation pixels, is joined
Pixel is examined more than or equal to object pixel and fluctuation threshold sum, then the pixel value of the corresponding binaryzation pixel of reference pixel is 1, ginseng
Examine pixel and deduct the difference after fluctuation threshold less than object pixel, then the pixel value of the corresponding binaryzation pixel of reference pixel is ﹣
1, the pixel value of the corresponding binaryzation pixel of reference pixel of other values is 0；The sub- equipment of matrix-split sets with processes pixel
Standby connection, for by the corresponding binaryzation matrix conversion of each object pixel into a positive binaryzation matrix and a negative two-value
Change matrix, positive binaryzation matrix is made up of 8 binaryzation pixel values, negative binaryzation matrix is also made up of 8 binaryzation pixel values,
Each binaryzation pixel value of positive binaryzation matrix deducts the binaryzation pixel value of negative binaryzation matrix relevant position and can obtain
To the pixel value of the binaryzation pixel of correspondence binaryzation matrix relevant position；The decimal system changes sub- equipment and the sub- equipment of matrix-split
Connection, for all binaryzation pixel values of the corresponding positive binaryzation matrix of each object pixel to be pressed into it in positive binaryzation square
Position in battle array constitutes a binary number as the positive binary number of target using first left and then right first up and then down again order, then by mesh
Marking positive binary number, to change into decimal number corresponding negative by each object pixel as the positive decimal number of target, to be additionally operable to
All binaryzation pixel values of binaryzation matrix are by its position in negative binaryzation matrix with first left and then right first up and then down again
Order constitute a binary number as target negative binary number, then by target negative binary number change into decimal number using as
Target bears decimal number；Characteristic vector obtains sub- equipment and is connected with histogram equalization equipment and the sub- equipment of decimal system conversion respectively,
For the pixel value of each object pixel in equilibrium figures picture to be substituted for into the corresponding positive goal decimal number of the object pixel simultaneously
The corresponding positive goal decimal number of all object pixels is constituted into just one-dimensional spy according to position of the object pixel in equilibrium figures picture
Vector is levied, as the output of positive goal characteristic vector, is additionally operable to be substituted for the pixel value of each object pixel in equilibrium figures picture
The corresponding negative target decimal number of the object pixel and according to position of the object pixel in equilibrium figures picture by all object pixels
Corresponding negative target decimal number constitutes negative one dimensional feature vector, used as the output of negative target feature vector；Characteristic vector is more sub
Equipment obtains respectively sub- equipment with characteristic vector and IP unpacks equipment and is connected, for by positive goal characteristic vector respectively with each base
Accurate positive characteristic vector is matched, and negative target feature vector is matched respectively with each benchmark negative feature vector, and the two is all
The corresponding authorized user's title of the positive characteristic vector of benchmark that the match is successful and matches is right with the benchmark negative feature vector for matching
When authorized user's title for answering is identical, then recognition of face pass signal and corresponding with the positive characteristic vector of the benchmark for matching is exported
Authorized user's title, otherwise will output recognition of face failure signal；
IP unpacks equipment, for being connected with long-range data server network, is received at data server by network
IP packets, and IP packets are unpacked to obtain 6LowPAN packets；Wherein, IP packets are that 6LowPAN packets are entered
Row beats the packet obtained after IP bags, and the load in 6LowPAN packets includes that each benchmark at data server is just special
Vector sum each benchmark negative feature vector is levied, the head in 6LowPAN packets is compressed data, the 6LowPAN numbers after decompression
It is used to parse the load in 6LowPAN packets according to the head in bag；Wherein, the positive characteristic vector of each benchmark is right
Corresponding authorized user's benchmark face-image carry out in advance with the positive characteristic vector pickup of feature extracting device same operation and obtain
Vector, each benchmark negative feature vector is that corresponding authorized user's benchmark face-image is carried out in advance and feature extracting device
The vector that the negative feature vector of same operation is extracted and obtained；
Edge sensing equipment, unpacks equipment and is connected with IP, for receiving the 6LowPAN packets that IP unpacks equipment output, obtains
The head of the 6LowPAN packets of compressed data is rendered as, after decompressing the head of 6LowPAN packets to be decompressed
Head in 6LowPAN packets；
6LowPAN unpacks equipment, is connected with edge sensing equipment, for receiving 6LowPAN packets to obtain 6LowPAN data
Load in bag, and the load in 6LowPAN packets is solved based on the head in the 6LowPAN packets after decompression
Analysis, to obtain the positive characteristic vector of each benchmark and each benchmark negative feature vector；
Wherein, alternatively, Gaussian smoothing equipment is replaced using wavelet filtering equipment, wavelet filtering equipment connects with intensity compensation devices
Connect to receive brightness adjustment image, wavelet filtering is carried out to brightness adjustment image and is processed to obtain smoothed image；
High-definition camera also includes photoflash controller and flash lamp；
High-definition camera also includes luminance sensor, for detecting real time environment brightness.
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Cited By (2)
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| CN107896318A (en) * | 2017-08-18 | 2018-04-10 | 魏芳 | WIFI network adaptive connection system |
| CN108665469A (en) * | 2017-11-09 | 2018-10-16 | 王涛 | A kind of vision impairment monitoring alarm method |
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| US20120170817A1 (en) * | 2010-12-31 | 2012-07-05 | Altek Corporation | Vehicle apparatus control system and method thereof |
| CN102582578A (en) * | 2011-09-28 | 2012-07-18 | 福州海景科技开发有限公司 | Anti-theft system for vehicle based on infrared and face recognition technology |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US20120170817A1 (en) * | 2010-12-31 | 2012-07-05 | Altek Corporation | Vehicle apparatus control system and method thereof |
| CN102582578A (en) * | 2011-09-28 | 2012-07-18 | 福州海景科技开发有限公司 | Anti-theft system for vehicle based on infrared and face recognition technology |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107896318A (en) * | 2017-08-18 | 2018-04-10 | 魏芳 | WIFI network adaptive connection system |
| CN108665469A (en) * | 2017-11-09 | 2018-10-16 | 王涛 | A kind of vision impairment monitoring alarm method |
| CN108665469B (en) * | 2017-11-09 | 2021-08-17 | 胡秀川 | Vision impairment monitoring and alarming method |
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