CN107241243B - Intelligent home safety monitoring system - Google Patents

Intelligent home safety monitoring system Download PDF

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CN107241243B
CN107241243B CN201710420949.0A CN201710420949A CN107241243B CN 107241243 B CN107241243 B CN 107241243B CN 201710420949 A CN201710420949 A CN 201710420949A CN 107241243 B CN107241243 B CN 107241243B
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不公告发明人
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Shandong Liwang Petroleum Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B19/00—Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H04N5/265—Mixing
    • 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 provides an intelligent home safety monitoring system which comprises a camera, a video processor, a sensor group, an intelligent identification terminal, a wireless transmission network and a client side, wherein the camera is connected with the video processor; the camera comprises a high-resolution camera and a low-resolution camera which are respectively used for acquiring a real-time face image and an environment image in a monitoring area; the video processor is used for synthesizing the real-time face image and the environment image to obtain a high-definition monitoring image; the intelligent identification terminal is used for identifying the high-definition monitoring image and abnormal information in the information collected by the sensor group and sending an early warning signal to the client through the wireless transmission network; the wireless transmission network is used for wirelessly transmitting the high-definition monitoring images and the information collected by the sensor group to the client. The invention can monitor various information in the home environment in real time, has comprehensive functions and can provide comfortable, intelligent and safe home life for users.

Description

Intelligent home safety monitoring system
Technical Field
The invention relates to the field of intelligent home furnishing, in particular to an intelligent home furnishing safety monitoring system.
Background
The household monitoring system in the prior art generally adopts an infrared probe to monitor at night in the aspect of theft prevention, and also adopts a camera to monitor indoors, so that when theft or other conditions occur, after-the-fact evidence is provided for a host, but the accident is remedied after the dangerous case occurs, and sometimes the loss can not be recovered for the host, and an intelligent household safety monitoring system is needed to give an early warning before the accident occurs, so that the dangerous case is prevented.
Disclosure of Invention
Aiming at the problems, the invention aims to provide an intelligent home safety monitoring system.
The purpose of the invention is realized by adopting the following technical scheme:
an intelligent home security monitoring system comprises a camera, a video processor, a sensor group, an intelligent identification terminal, a wireless transmission network and a client; the camera comprises a high-resolution camera and a low-resolution camera which are respectively used for acquiring real-time human face images and environment images in a monitoring area, and is connected with the video processor in a wired manner and installed in a home environment; the video processor is used for synthesizing the real-time face image and the environment image to obtain a high-definition monitoring image; the intelligent identification terminal is in wired connection with the video processor and the sensor group, and is used for identifying high-definition monitoring images and abnormal information in information collected by the sensor group and sending early warning signals to a client through the wireless transmission network; the wireless transmission network is used for wirelessly transmitting the high-definition monitoring images and the information collected by the sensor group to the client.
The invention has the beneficial effects that: the invention can monitor various information in the home environment in real time, has comprehensive functions and can provide comfortable, intelligent and safe home life for users.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a block diagram of the framework of the present invention;
FIG. 2 is a block diagram of a frame of a video processor of the present invention;
fig. 3 is a frame configuration diagram of the sensor group of the present invention.
Reference numerals:
the system comprises a camera 1, a video processor 2, a sensor group 3, an intelligent identification terminal 4, a wireless transmission network 5, a client 6, a high-resolution camera 10, a low-resolution camera 11, a monitoring image denoising module 201, a monitoring image decomposition module 202, a monitoring image synthesis module 203, a carbon monoxide sensor 301, a carbon dioxide sensor 302, a temperature sensor 303, a humidity sensor 304, a dust sensor 305, a smoke sensor 306 and a vibration sensor 307.
Detailed Description
The invention is further described in connection with the following application scenarios.
Referring to fig. 1, the system comprises a camera 1, a video processor 2, a sensor group 3, an intelligent identification terminal 4, a wireless transmission network 5 and a client 6; the camera 1 comprises a high-resolution camera 10 and a low-resolution camera 11 which are respectively used for acquiring real-time human face images and environment images in a monitoring area, and the camera 1 is connected with the video processor 2 in a wired mode and is installed in a home environment; the video processor 2 is used for synthesizing the real-time face image and the environment image to obtain a high-definition monitoring image; the intelligent identification terminal 4 is in wired connection with the video processor 2 and the sensor group 3, and is used for identifying high-definition monitoring images and abnormal information in information acquired by the sensor group and sending early warning signals to the client 6 through the wireless transmission network 5; the wireless transmission network 5 is used for wirelessly transmitting the high-definition monitoring images and the information collected by the sensor group 3 to the client.
Preferably, as shown in fig. 2, the sensor group includes a carbon monoxide sensor, a carbon dioxide sensor, a temperature sensor, a humidity sensor, a dust sensor, a smoke sensor and a vibration sensor, which are respectively used for acquiring carbon monoxide concentration, carbon dioxide concentration, temperature, humidity, dust concentration, smoke concentration and vibration intensity information in the household environment.
Preferably, the abnormal information in the high-definition monitoring image and the information collected by the sensor group comprises intrusion of strangers, carbon monoxide leakage, too high carbon dioxide concentration, too high or too low room temperature, too high or too low humidity, too high dust concentration and earthquakes of more than 5 grades.
According to the embodiment of the invention, various information in the home environment can be monitored in real time, the functions are comprehensive, and comfortable, intelligent and safe home life can be provided for users.
Preferably, as shown in fig. 3, the video processor includes a monitor image denoising module, a monitor image decomposition module and a monitor image synthesis module;
the monitoring image denoising module performs wavelet transformation processing on a face image with noise and an environment image to obtain corresponding wavelet coefficients, the obtained wavelet coefficients comprise a noiseless wavelet coefficient and a noise wavelet coefficient, thresholding processing is performed on the obtained wavelet coefficients by adopting an improved threshold function to filter the noise wavelet coefficient to obtain the noiseless wavelet coefficient, and finally, the noiseless wavelet coefficients are obtained after thresholding processing to reconstruct the face image and the environment image to obtain the noiseless face image and the noiseless environment image, wherein the adopted improved threshold function is as follows:
Figure BDA0001314909440000031
Figure BDA0001314909440000032
in the formula (I), the compound is shown in the specification,
Figure BDA0001314909440000033
representing a noise-free wavelet coefficient, wherein f is a wavelet coefficient obtained by performing wavelet transformation processing on a face image with noise and an environment image, sgn (·) is a sign function, x is a variable of the sign function, j and k are adjustable parameters, mu is a wavelet coefficient threshold value and is a noise standard deviation, and P and Q are the width and height of the face image with noise and the environment image with noise;
this improved threshold function is a hard threshold function when j is 0 or k is 1, and a soft threshold function when j is 1 and k is 1.
In the embodiment of the invention, the noise wavelet coefficient is filtered by the improved threshold function, the noise-free wavelet coefficient is reserved, the noise-free face image and the environment image can be obtained when the face image and the environment image are reconstructed, meanwhile, the improved threshold function can be between the soft threshold function and the hard threshold function by adjusting the parameters j and k, the defects of discontinuity of the wavelet coefficient obtained by processing the hard threshold function and the calculation deviation of the soft threshold function on the wavelet coefficient are overcome, and the efficiency and the accuracy of the denoising processing on the face image and the environment image can be improved.
Preferably, the monitoring image decomposition module includes:
(1) respectively decomposing the noise-free face image and the noise-free environment image by adopting non-subsampled Contourlet transform (NSCT) to obtain a low-frequency sub-band coefficient T1 Low(p, q) and T2 Low(p, q), and a respective series of high frequency subband coefficients
Figure BDA0001314909440000034
And
Figure BDA0001314909440000035
wherein a is more than or equal to 1 and less than or equal to A, and b is more than or equal to 1 and less than or equal to ba；
T1 Low(p, q) and T2 Low(p, q) respectively represent the noise-free face image T1And a noise-free ambient image T2Low frequency subband coefficients at pixel points (p, q),
Figure BDA0001314909440000036
and
Figure BDA0001314909440000037
representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band coefficient of the (a) th scale in the (b) th direction at the pixel point (p, q), A is the scale degree, a represents the (a) th scale, b is the (b) th direction, baThe number of directions in the a scale is shown;
(2) sub-band coefficients obtained by decomposing the pixel points at (p, q) through NSCT are compared with sub-band coefficient values of 4 surrounding pixel points, the activity of the pixel points of the two noiseless images is calculated point by using a user-defined activity calculation formula, and the noiseless face image T is used1And a noise-free ambient image T2The high-frequency subband coefficient is subjected to activity calculation to obtain the activity of the high-frequency subband of the pixel point (p, q), and the user-defined activity calculation formula is as follows:
Figure BDA0001314909440000041
Figure BDA0001314909440000042
in the formula (I), the compound is shown in the specification,
Figure BDA0001314909440000043
and
Figure BDA0001314909440000044
respectively representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band activity of the b-th direction of the a-th scale of the middle (q) pixel point,
Figure BDA0001314909440000045
and
Figure BDA0001314909440000046
representing a noise-free face image T1And a noise-free ambient image T2High frequency subband coefficients at (p, q) in the (b) th direction of the a-th scale;
(3) similarly, by using a user-defined liveness calculation formula, the high-frequency subband coefficient is converted into a low-frequency subband coefficient, and the liveness of the low-frequency subbands of the two noiseless images is calculated to obtain the noiseless face image T1And a noise-free ambient image T2Activity R of low frequency sub-band of pixel point at (p, q)1 Low(p, q) and R2 Low(p,q)。
According to the embodiment of the invention, the liveness of the pixel points of the noise-free face image and the noise-free environment image is calculated point by point, because the face image is shot by the high-resolution camera, naturally, the liveness of the pixel points of the face partial image is higher, and the other parts of the face partial image are shot by the low-resolution camera, so that the combination is beneficial to reducing the space occupation of the monitoring image, the speed is higher when the intelligent recognition terminal recognizes the face, and the recognition accuracy is ensured.
Preferably, the monitoring image synthesizing module includes:
(1) for noise-free face image T1And a noise-free ambient image T2Comparing the liveness at the point (p, q) to obtain a corresponding liveness comparison result, re-valuing the subband coefficient according to the liveness comparison result to obtain a new high-frequency subband coefficient and a new low-frequency subband coefficient, and taking the new subband coefficient as the subband coefficient of the synthesized high-definition monitoring image, specifically:
Figure BDA0001314909440000051
in the formula, T (p, q) is a subband coefficient of the synthesized high-definition monitoring image after the value is re-taken at the point (p, q), and R1(p, q) and R2(p, q) are the noise-free face image T respectively1And a noise-free ambient image T2Activity of pixels at center (p, q), R1(p, q) includes R1 Low(p, q) and
Figure BDA0001314909440000052
comprising R2 Low(p, q) and
Figure BDA0001314909440000053
and T2(p, q) are the noise-free face image T respectively1And a noise-free ambient image T2Subband coefficient at point (p, q), T1(p, q) includes T1 Low(p, q) and
Figure BDA0001314909440000054
T2(p, q) includes T2 Low(p, q) and
Figure BDA0001314909440000055
T1 Low(p, q) and T2 Low(p, q) respectively represent the noise-free face image T1And a noise-free ambient image T2Low frequency subband coefficients at pixel points (p, q),
Figure BDA0001314909440000056
and
Figure BDA0001314909440000057
representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band coefficient of the b-th direction of the a-th scale at the pixel point (P, Q) is respectively expressed by P and Q, the width and the height of the two noiseless images are respectively expressed by P and Q, beta is an adjusting threshold value, and beta is set to be 0.5;
when R is1(p,q)＝R1 LowAt (p, q), R2(p,q)＝R2 Low(p,q)，T1(p,q)＝T1 Low(p,q)，T2(p,q)＝T2 Low(p, q) when
Figure BDA0001314909440000058
When the temperature of the water is higher than the set temperature,
Figure BDA0001314909440000059
Figure BDA00013149094400000510
(2) and (4) taking the obtained new high-frequency sub-band coefficient and the new low-frequency sub-band coefficient as the high-frequency sub-band coefficient and the low-frequency sub-band coefficient of the synthesized image, and reconstructing the image through NSCT inverse transformation to obtain the synthesized high-definition monitoring image.
According to the embodiment of the invention, the high-resolution face image and the environment image are synthesized, the synthesized high-resolution monitoring image can highlight the face, the identification of the face by the intelligent identification terminal and the identification of people when the user looks over the monitoring image are both very beneficial, and the low-resolution environment image is adopted for the rest images except the face image, so that the interference of irrelevant factors is reduced.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (2)

1. An intelligent home security monitoring system is characterized by comprising a camera, a video processor, a sensor group, an intelligent identification terminal, a wireless transmission network and a client; the camera comprises a high-resolution camera and a low-resolution camera which are respectively used for acquiring real-time human face images and environment images in a monitoring area, and the camera is in wired connection with the video processor; the video processor is used for synthesizing the real-time face image and the environment image to obtain a high-definition monitoring image; the intelligent identification terminal is in wired connection with the video processor and the sensor group, and is used for identifying high-definition monitoring images and abnormal information in information collected by the sensor group and sending early warning signals to a client through the wireless transmission network; the wireless transmission network is used for wirelessly transmitting the high-definition monitoring image and the information acquired by the sensor group to the client;
the sensor group comprises a carbon monoxide sensor, a carbon dioxide sensor, a temperature sensor, a humidity sensor, a dust sensor, a smoke sensor and a vibration sensor, and the sensor group is respectively used for acquiring the information of carbon monoxide concentration, carbon dioxide concentration, temperature, humidity, dust concentration, smoke concentration and vibration intensity in a home environment;
abnormal information in the high-definition monitoring image and the information collected by the sensor group comprises intrusion of strangers, carbon monoxide leakage, overhigh carbon dioxide concentration, overhigh or overlow room temperature, overhigh or overlow humidity, overhigh dust concentration and earthquakes of more than 5 grades;
the video processor comprises a monitoring image denoising module, a monitoring image decomposition module and a monitoring image synthesis module;
the monitoring image denoising module performs wavelet transformation processing on a face image with noise and an environment image to obtain corresponding wavelet coefficients, the obtained wavelet coefficients comprise a noiseless wavelet coefficient and a noise wavelet coefficient, thresholding processing is performed on the obtained wavelet coefficients by adopting an improved threshold function to filter the noise wavelet coefficient to obtain the noiseless wavelet coefficient, and finally the noiseless face image and the noiseless environment image are reconstructed by using the noiseless wavelet coefficients obtained after thresholding processing to obtain the noiseless face image and the noiseless environment image, wherein the adopted improved threshold function is as follows:
Figure FDA0002610001370000011
Figure FDA0002610001370000012
in the formula (I), the compound is shown in the specification,
Figure FDA0002610001370000013
representing a noise-free wavelet coefficient, wherein f is a wavelet coefficient obtained by performing wavelet transformation processing on a face image with noise and an environment image, sgn (·) is a sign function, x is a variable of the sign function, j and k are adjustable parameters, mu is a wavelet coefficient threshold value and is a noise standard deviation, and P and Q are the width and height of the face image with noise and the environment image with noise;
the monitoring image decomposition module comprises:
(1) respectively decomposing the noise-free face image and the noise-free environment image by adopting non-subsampled Contourlet transform (NSCT) to obtain a low-frequency sub-band coefficient T1 Low(p, q) and T2 Low(p, q), and a respective series of high frequency subband coefficients
Figure FDA0002610001370000021
And
Figure FDA0002610001370000022
wherein a is more than or equal to 1 and less than or equal to A, and b is more than or equal to 1 and less than or equal to ba；
Wherein, T1 Low(p, q) and T2 Low(p, q) respectively represent the noise-free face image T1And a noise-free ambient image T2Low frequency subband coefficients at pixel points (p, q),
Figure FDA0002610001370000023
and
Figure FDA0002610001370000024
representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band coefficient of the (a) th scale in the (b) th direction at the pixel point (p, q), A is the scale degree, a represents the (a) th scale, b is the (b) th direction, baThe number of directions in the a scale is shown;
(2) sub-band coefficients obtained by decomposing the pixel points at (p, q) through NSCT are compared with sub-band coefficient values of 4 surrounding pixel points, the activity of the pixel points of the two noiseless images is calculated point by using a user-defined activity calculation formula, and the noiseless face image T is used1And a noise-free ambient image T2The high-frequency subband coefficient is subjected to activity calculation to obtain the activity of the high-frequency subband of the pixel point (p, q), and the user-defined activity calculation formula is as follows:
Figure FDA0002610001370000025
Figure FDA0002610001370000031
in the formula (I), the compound is shown in the specification,
Figure FDA0002610001370000032
and
Figure FDA0002610001370000033
respectively representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band activity of the b-th direction of the a-th scale of the middle (p, q) pixel point,
Figure FDA0002610001370000034
and
Figure FDA0002610001370000035
representing a noise-free face image T1And a noise-free ambient image T2High frequency subband coefficients at (p, q) in the (b) th direction of the a-th scale;
(3) similarly, by using a user-defined liveness calculation formula, the high-frequency subband coefficient is converted into a low-frequency subband coefficient, and the liveness of the low-frequency subbands of the two noiseless images is calculated to obtain the noiseless face image T1And a noise-free ambient image T2Activity R of low frequency sub-band of pixel point at (p, q)1 Low(p, q) and R2 Low(p,q)。
2. The smart home security monitoring system of claim 1, wherein the monitoring image synthesis module comprises:
(1) for noise-free face image T1And a noise-free ambient image T2Comparing the liveness at the point (p, q) to obtain a corresponding liveness comparison result, re-valuing the subband coefficient according to the liveness comparison result to obtain a new high-frequency subband coefficient and a new low-frequency subband coefficient, and taking the new subband coefficient as the subband coefficient of the synthesized high-definition monitoring image, specifically:
Figure FDA0002610001370000036
in the formula, T (p, q) is a subband coefficient of the synthesized high-definition monitoring image after the value is re-taken at the point (p, q), and R1(p, q) and R2(p, q) are the noise-free face image T respectively1And a noise-free ambient image T2Activity of pixels at center (p, q), R1(p, q) includes R1 Low(p, q) and
Figure FDA0002610001370000041
R2(p, q) includes R2 Low(p, q) and
Figure FDA0002610001370000042
T1(p, q) and T2(p, q) are the noise-free face image T respectively1And a noise-free ambient image T2Subband coefficient at point (p, q), T1(p, q) includes T1 Low(p, q) and
Figure FDA0002610001370000043
T2(p, q) includes T2 Low(p, q) and
Figure FDA0002610001370000044
T1 Low(p, q) and T2 Low(p, q) respectively represent the noise-free face image T1And a noise-free ambient image T2Low frequency subband coefficients at pixel points (p, q),
Figure FDA0002610001370000045
and
Figure FDA0002610001370000046
representing a noise-free face image T1And a noise-free ambient image T2The high-frequency sub-band coefficient of the b-th direction of the a-th scale at the pixel point (P, Q), P and Q respectively represent the width and height of the two noiseless images, beta is an adjustment threshold value, and beta<1；
When R is1(p,q)＝R1 LowAt (p, q), R2(p,q)＝R2 Low(p,q)，T1(p,q)＝T1 Low(p,q)，T2(p,q)＝T2 Low(p, q) when
Figure FDA0002610001370000047
When the temperature of the water is higher than the set temperature,
Figure FDA0002610001370000048
Figure FDA0002610001370000049
(2) and (4) taking the obtained new high-frequency sub-band coefficient and the new low-frequency sub-band coefficient as the high-frequency sub-band coefficient and the low-frequency sub-band coefficient of the synthesized image, and reconstructing the image through NSCT inverse transformation to obtain the synthesized high-definition monitoring image.
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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103338362A (en) * 2013-07-26 2013-10-02 深圳市融创天下科技股份有限公司 Event handling method and system based on video monitoring system

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US7260272B2 (en) * 2003-07-10 2007-08-21 Samsung Electronics Co.. Ltd. Method and apparatus for noise reduction using discrete wavelet transform

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Publication number Priority date Publication date Assignee Title
CN103338362A (en) * 2013-07-26 2013-10-02 深圳市融创天下科技股份有限公司 Event handling method and system based on video monitoring system

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Title
物联网下的嵌入式家居安全监控***设计与实现;陈德裕等;《传感器与微***》;20121231;第31卷(第9期);105-108页 *

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