CN109177923A - A kind of vehicle security drive monitoring method and system - Google Patents
A kind of vehicle security drive monitoring method and system Download PDFInfo
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- CN109177923A CN109177923A CN201811007532.2A CN201811007532A CN109177923A CN 109177923 A CN109177923 A CN 109177923A CN 201811007532 A CN201811007532 A CN 201811007532A CN 109177923 A CN109177923 A CN 109177923A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
- B60R25/20—Means to switch the anti-theft system on or off
- B60R25/25—Means to switch the anti-theft system on or off using biometry
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Abstract
The present invention provides a kind of vehicle security drive monitoring method and system, the present invention can carry out recognition of face to the driver in the driver and running car for entering automobile, and alarm when finding that other staff are prepared to enter into automobile or driving, advantageously ensure that the safe driving of automobile.
Description
Technical field
The present invention relates to safe driving technical field more particularly to a kind of vehicle security drive monitoring methods and system.
Background technique
Currently, in order to be managed to the driver for entering automobile, it is main by door control system to the door body of automobile into
Row control.However, such as other staff obtain the access card or password for entering automobile, then still it is able to enter in automobile.
In addition, existing automobile can not carry out real-time monitoring to personnel, the safety for being unfavorable for automobile is driven in the driving procedure of automobile
It sails.Therefore, in view of the above-mentioned problems, it is necessary to propose further solution.
Summary of the invention
The purpose of the present invention is to provide a kind of vehicle security drive monitoring method and systems, are deposited in the prior art with overcoming
Deficiency.
For achieving the above object, the present invention provides a kind of vehicle security drive monitoring method comprising following steps:
S1, it recognizes whether to need the driver into vehicle, such as identify successfully, continuously acquire driver's
Facial image extracts the condition code of facial image, when the condition code of extraction is consistent with the condition code of the facial image of storage, beats
Door opening；
S2, identification steering position whether there is driver, such as identify successfully, continuously acquire the face figure of driver
Picture extracts the condition code of facial image, and when the condition code of extraction is consistent with the condition code of the facial image of storage, automobile is opened
It is dynamic；
S3, the speed for detecting running car continuously acquire the facial image of driver if speed is lower than 30KM/h,
The condition code for extracting facial image is not sounded an alarm when the condition code of extraction is consistent with the condition code of the facial image of storage,
Otherwise it alarms；
S4, the speed for detecting running car continuously acquire the facial image of driver if speed is higher than 30KM/h,
By comparing the facial image of acquisition, driver's eyes opening and closing frequency and the frequency that mouth opens are identified, when eyes opening and closing
When the frequency that frequency and mouth open is not up to the threshold value set, does not sound an alarm, otherwise alarm.
As the improvement of vehicle security drive monitoring method of the invention, described document information is corresponding with human face five-sense-organ
Position data and face mask data.
As the improvement of vehicle security drive monitoring method of the invention, the vehicle security drive monitoring method further includes
Processing is filtered to the face image data of acquisition:
According to the face image data of acquisition, it is full to calculate local energy spectrum gradient, histogram of gradients extension and maximum chrominance
With；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, whole picture is counted
The ratio that pixel is obscured in image, effectively filters face image data.
As the improvement of vehicle security drive monitoring method of the invention, the local energy spectrum gradient is as follows
It calculates:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope.Largely studies have shown that scheming naturally
α is about 2 as in, and fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as part and global-alpha value
Proportional difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the ladders of the gauss hybrid models of Gauss description part
Degree distribution: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, it is full to obtain maximum chrominance
With:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is that saturation degree is maximum in global image
Value.
For achieving the above object, the present invention provides a kind of vehicle security drive monitoring system comprising: the first camera shooting
Machine, the second video camera, velocity sensor, alarm and host, first video camera, the second video camera and the host number
According to transmission, the velocity sensor, alarm and the host signal are transmitted；
First video camera recognizes whether to need the driver into vehicle, such as identifies successfully, continuously adopt
Collect the facial image of driver, the host extracts the condition code of facial image, stores when the condition code and host of extraction
When the condition code of facial image is consistent, car door is opened；
The second video camera identification steering position whether there is driver, such as identify successfully, continuously acquisition drives
The facial image of personnel, the host extract the condition code of facial image, when the face figure of condition code and the host storage of extraction
When the condition code of picture is consistent, automobile starting；
The speed of the velocity sensor detection running car, if speed is lower than 30KM/h, second video camera is continuous
Ground acquires the facial image of driver, and the host extracts the condition code of facial image, when condition code and the host of extraction are deposited
When the condition code of the facial image of storage is consistent, the alarm is not sounded an alarm, and is otherwise alarmed；
The speed of the velocity sensor detection running car, if speed is higher than 30KM/h, second video camera is continuous
Ground acquires the facial image of driver, and the host identifies the opening and closing of driver's eyes by comparing the facial image acquired
The frequency that frequency and mouth open, when the frequency of eyes opening and closing frequency and mouth opening is not up to the threshold value set, institute
It states alarm not sound an alarm, otherwise alarm.
As the improvement of vehicle security drive monitoring system of the invention, described document information is corresponding with human face five-sense-organ
Position data and face mask data.
As changing for vehicle security drive monitoring system of the invention, vehicle security drive monitoring system is also used to adopting
The face image data of collection is filtered processing:
According to the face image data of acquisition, it is full to calculate local energy spectrum gradient, histogram of gradients extension and maximum chrominance
With；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, whole picture is counted
The ratio that pixel is obscured in image, effectively filters face image data.
As changing for vehicle security drive monitoring system of the invention, the local energy spectrum gradient is counted as follows
It calculates:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope.Largely studies have shown that scheming naturally
α is about 2 as in, and fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as part and global-alpha value
Proportional difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the ladders of the gauss hybrid models of Gauss description part
Degree distribution: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, it is full to obtain maximum chrominance
With:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is that saturation degree is maximum in global image
Value.
Compared with prior art, the beneficial effects of the present invention are: the present invention can to enter automobile driver and
Driver in running car carries out recognition of face, and when finding that other staff are prepared to enter into automobile or driving into
Row alarm, advantageously ensures that the safe driving of automobile.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The some embodiments recorded in invention, for those of ordinary skill in the art, without creative efforts,
It is also possible to obtain other drawings based on these drawings.
Fig. 1 is the method flow schematic diagram of a specific embodiment of vehicle security drive monitoring method of the invention.
Specific embodiment
The present invention is described in detail for each embodiment shown in reference to the accompanying drawing, but it should be stated that, these
Embodiment is not limitation of the present invention, those of ordinary skill in the art according to these embodiments made by function, method,
Or equivalent transformation or substitution in structure, all belong to the scope of protection of the present invention within.
As shown in Figure 1, vehicle security drive monitoring method of the invention includes the following steps:
S1, it recognizes whether to need the driver into vehicle, such as identify successfully, continuously acquire driver's
Facial image extracts the condition code of facial image, when the condition code of extraction is consistent with the condition code of the facial image of storage, beats
Door opening.
So in order to carry out recognition of face to the driver for entering automobile, other staff is avoided to enter to fall in automobile.
Preferably, described document information is position data corresponding with human face five-sense-organ and face mask data.
S2, identification steering position whether there is driver, such as identify successfully, continuously acquire the face figure of driver
Picture extracts the condition code of facial image, and when the condition code of extraction is consistent with the condition code of the facial image of storage, automobile is opened
It is dynamic.
So in order to carry out recognition of face to the driver of driving, other staff is avoided to drive a car.It is preferred that
Ground, described document information are position data corresponding with human face five-sense-organ and face mask data.
S3, the speed for detecting running car continuously acquire the facial image of driver if speed is lower than 30KM/h,
The condition code for extracting facial image is not sounded an alarm when the condition code of extraction is consistent with the condition code of the facial image of storage,
Otherwise it alarms.
So in order to preventing driver to be held as a hostage or be not to drive in person.Preferably, described document information is and face five
The corresponding position data of official and face mask data.
S4, the speed for detecting running car continuously acquire the facial image of driver if speed is higher than 30KM/h,
By comparing the facial image of acquisition, driver's eyes opening and closing frequency and the frequency that mouth opens are identified, when eyes opening and closing
When the frequency that frequency and mouth open is not up to the threshold value set, does not sound an alarm, otherwise alarm.
The generation of so in order to prevent fatigue driving the case where guarantees the safe driving of automobile.
In addition, the vehicle security drive monitoring method further includes being filtered processing to the face image data of acquisition:
According to the face image data of acquisition, it is full to calculate local energy spectrum gradient, histogram of gradients extension and maximum chrominance
With；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, whole picture is counted
The ratio that pixel is obscured in image, effectively filters face image data.
Wherein, the local energy spectrum gradient calculates as follows:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope.Largely studies have shown that scheming naturally
α is about 2 as in, and fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as part and global-alpha value
Proportional difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the ladders of the gauss hybrid models of Gauss description part
Degree distribution: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, it is full to obtain maximum chrominance
With:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is that saturation degree is maximum in global image
Value.
Based on identical inventive concept, the present invention also provides a kind of vehicle security drive monitoring systems comprising: first takes the photograph
Camera, the second video camera, velocity sensor, alarm and host, first video camera, the second video camera and the host
Data transmission, the velocity sensor, alarm and the host signal transmit；
First video camera recognizes whether to need the driver into vehicle, such as identifies successfully, continuously adopt
Collect the facial image of driver, the host extracts the condition code of facial image, stores when the condition code and host of extraction
When the condition code of facial image is consistent, car door is opened；Wherein, described document information be position data corresponding with human face five-sense-organ with
And face mask data.
The second video camera identification steering position whether there is driver, such as identify successfully, continuously acquisition drives
The facial image of personnel, the host extract the condition code of facial image, when the face figure of condition code and the host storage of extraction
When the condition code of picture is consistent, automobile starting；Wherein, described document information is position data corresponding with human face five-sense-organ and face
Outline data.
The speed of the velocity sensor detection running car, if speed is lower than 30KM/h, second video camera is continuous
Ground acquires the facial image of driver, and the host extracts the condition code of facial image, when condition code and the host of extraction are deposited
When the condition code of the facial image of storage is consistent, the alarm is not sounded an alarm, and is otherwise alarmed；Wherein, described document information
For position data corresponding with human face five-sense-organ and face mask data.
The speed of the velocity sensor detection running car, if speed is higher than 30KM/h, second video camera is continuous
Ground acquires the facial image of driver, and the host identifies the opening and closing of driver's eyes by comparing the facial image acquired
The frequency that frequency and mouth open, when the frequency of eyes opening and closing frequency and mouth opening is not up to the threshold value set, institute
It states alarm not sound an alarm, otherwise alarm.
In addition, vehicle security drive monitoring system is also used to be filtered processing to the face image data of acquisition:
According to the face image data of acquisition, it is full to calculate local energy spectrum gradient, histogram of gradients extension and maximum chrominance
With；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, whole picture is counted
The ratio that pixel is obscured in image, effectively filters face image data.
Wherein, the local energy spectrum gradient calculates as follows:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope.Largely studies have shown that scheming naturally
α is about 2 as in, and fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as part and global-alpha value
Proportional difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the ladders of the gauss hybrid models of Gauss description part
Degree distribution: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, it is full to obtain maximum chrominance
With:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is that saturation degree is maximum in global image
Value.
In conclusion the present invention can carry out people to the driver in the driver and running car for entering automobile
Face identification, and alarm when finding that other staff are prepared to enter into automobile or driving, advantageously ensure that automobile
Safe driving.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.Any reference signs in the claims should not be construed as limiting the involved claims.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only wrapped
Containing an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should
It considers the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms those skilled in the art
The other embodiments being understood that.
Claims (8)
1. a kind of vehicle security drive monitoring method, which is characterized in that the vehicle security drive monitoring method includes following step
It is rapid:
S1, it recognizes whether to need the driver into vehicle, such as identifies successfully, continuously acquire the face of driver
Image extracts the condition code of facial image, when the condition code of extraction is consistent with the condition code of the facial image of storage, opens vehicle
Door；
S2, identification steering position whether there is driver, such as identify successfully, continuously acquire the facial image of driver,
The condition code for extracting facial image, when the condition code of extraction is consistent with the condition code of the facial image of storage, automobile starting；
S3, the speed for detecting running car continuously acquire the facial image of driver, extract if speed is lower than 30KM/h
The condition code of facial image does not sound an alarm, otherwise when the condition code of extraction is consistent with the condition code of the facial image of storage
It alarms；
S4, the speed for detecting running car continuously acquire the facial image of driver, pass through if speed is higher than 30KM/h
The facial image of acquisition is compared, driver's eyes opening and closing frequency and the frequency that mouth opens are identified, when eyes opening and closing frequency
And mouth open frequency be not up to set threshold value when, do not sound an alarm, otherwise alarm.
2. vehicle security drive monitoring method according to claim 1, which is characterized in that described document information be and face five
The corresponding position data of official and face mask data.
3. vehicle security drive monitoring method according to claim 1, which is characterized in that the vehicle security drive monitoring
Method further includes being filtered processing to the face image data of acquisition:
According to the face image data of acquisition, local energy spectrum gradient, histogram of gradients extension and maximum chrominance saturation are calculated；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, entire image is counted
In obscure pixel ratio, face image data is effectively filtered.
4. vehicle security drive monitoring method according to claim 3, which is characterized in that the local energy spectrum gradient is pressed
It is calculated according to following method:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope；It is a large amount of studies have shown that α in natural image
About 2, fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as the ratio of part and global-alpha value
Difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the gradients point of the gauss hybrid models of Gauss description part
Cloth: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, obtain maximum chrominance saturation:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is saturation degree maximum value in global image.
5. a kind of vehicle security drive monitoring system, which is characterized in that the vehicle security drive monitoring method includes: first to take the photograph
Camera, the second video camera, velocity sensor, alarm and host, first video camera, the second video camera and the host
Data transmission, the velocity sensor, alarm and the host signal transmit；
First video camera is recognized whether to need the driver into vehicle, such as be identified successfully, continuously acquisition is driven
The facial image of personnel is sailed, the host extracts the condition code of facial image, when the face of condition code and the host storage of extraction
When the condition code of image is consistent, car door is opened；
The second video camera identification steering position whether there is driver, such as identifies successfully, continuously acquires driver
Facial image, the host extracts the condition code of facial image, when the facial image of condition code and the host storage of extraction
When condition code is consistent, automobile starting；
The speed of the velocity sensor detection running car, if speed is lower than 30KM/h, second video camera is continuously adopted
Collect the facial image of driver, the host extracts the condition code of facial image, stores when the condition code and host of extraction
When the condition code of facial image is consistent, the alarm is not sounded an alarm, and is otherwise alarmed；
The speed of the velocity sensor detection running car, if speed is higher than 30KM/h, second video camera is continuously adopted
Collect the facial image of driver, the host identifies driver's eyes opening and closing frequency by comparing the facial image acquired
And the frequency that mouth opens, when the frequency of eyes opening and closing frequency and mouth opening is not up to the threshold value set, the report
Alert device does not sound an alarm, and otherwise alarms.
6. vehicle security drive monitoring system according to claim 5, which is characterized in that described document information be and face five
The corresponding position data of official and face mask data.
7. vehicle security drive monitoring system according to claim 5, which is characterized in that the vehicle security drive monitoring
System is also used to be filtered processing to the face image data of acquisition:
According to the face image data of acquisition, local energy spectrum gradient, histogram of gradients extension and maximum chrominance saturation are calculated；
According to local energy spectrum gradient, histogram of gradients extension and the maximum chrominance saturation being calculated, entire image is counted
In obscure pixel ratio, face image data is effectively filtered.
8. vehicle security drive monitoring method according to claim 7, which is characterized in that the local energy spectrum gradient is pressed
It is calculated according to following method:
The energy spectrum of NxN sized images is first calculated with discrete Fourier transform:
Then it converts to polar coordinates u=fcos θ, v=fsin θ, and calculates S (f, θ), obtain:
Wherein, A is the amplitude factor in an all directions, and α is energy spectrum slope；It is a large amount of studies have shown that α in natural image
About 2, fuzzy image has biggish α.Therefore the On Local Fuzzy degree of image can be described as the ratio of part and global-alpha value
Difference
Wherein, αpIt is local α, αoIt is global-alpha；
The histogram of gradients extension calculates as follows:
The gradient of each pixel of image is first calculated, then with containing there are two the gradients point of the gauss hybrid models of Gauss description part
Cloth: π0G(x；μ0, σ0)+π1G(x；μ1, σ1), wherein σ1>σ0；
According to gradient distribution, the specific formula for calculation of histogram of gradients extension is
Wherein, CpIt is topography's intensity value ranges, ε is the minimum number prevented except zero, and τ is a constant, takes 25；
The maximum chrominance saturation calculates as follows:
First calculate the saturation degree of each pixel:
Then compare local saturation maximum value and global saturation degree maximum value using following formula, obtain maximum chrominance saturation:
Wherein, max (sp) it is saturation degree maximum value in topography's block, max (so) it is saturation degree maximum value in global image.
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Application publication date: 20190111 |