CN103576660B - Smart Home method for supervising - Google Patents
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- CN103576660B CN103576660B CN201310565632.8A CN201310565632A CN103576660B CN 103576660 B CN103576660 B CN 103576660B CN 201310565632 A CN201310565632 A CN 201310565632A CN 103576660 B CN103576660 B CN 103576660B
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Abstract
The invention discloses a kind of Intelligent home monitoring system, comprise monitor terminal, parametric controller and information receiving terminal, described monitor terminal comprises digit camera and sound collector, carries out image and sound gathers and the data collected are sent to parametric controller to monitoring environment; Described parametric controller comprises image processing system and sound processing system, processes the image data set voice data received, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.The present invention adopts sound and image processing techniques to carry out omnibearing monitoring and nurse to domestic environment, the different requirements of modern's life to house security can be met, and carry out data processing and inversion in conjunction with multitude of different ways, guarantee accuracy rate and the validity of monitoring.
Description
Technical field
The present invention relates to the system of a kind of Smart Home monitoring, particularly relate to a kind of system and the method thereof that utilize image and voice recognition to carry out Household monitor.
Background technology
Along with the development and progress of society, on the material base of abundance, people start to pay close attention to a kind of more comfortable, convenient and intelligent life style and attitude.The concept of " Smart Home " embodies people to the pursuit of intelligentized comfortable life, meanwhile, people to the requirement of security also in continuous lifting.
Along with the development of society, demographic dividend fades away, aging population becomes increasingly conspicuous, and add that more and more faster city life rhythm allows younger generation have to drop into more time and energy on work, and the not free old man to family and child nurses and look after.
Existing Intelligent home monitoring system is mostly by carrying out security monitoring at detection instruments such as door, window installation infrared lines.Its function singleness, can not meet home furnishings intelligent monitoring to other demands such as the nurses of kinsfolk, its security is limited in addition, and lawless person is easy to removed by detection instrument and make supervisory system ineffective.
Summary of the invention
Technical matters to be solved by this invention is, a kind of Intelligent home monitoring system is provided, comprise monitor terminal, parametric controller and information receiving terminal it is characterized in that, described monitor terminal comprises digit camera and sound collector, carries out image and sound gathers and the data collected are sent to parametric controller to monitoring environment; Described parametric controller comprises image processing system and sound processing system, processes the image data set voice data received, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.
Further, described monitor terminal is intelligent robot, and described intelligent robot is equipped with sonar unit and can senses surrounding environment and assist intelligent monitoring to household.
Further, described monitor terminal for fixing camera, can be monitored by installing camera each corner to household in multiple corners of household.
Described method comprises:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
Step S1 comprises:
S11 transfers the picture pixels of shooting to HSV color space pattern by rgb color space pattern, adopts HSV can color combining information and textural characteristics, can improve discrimination power and can identification scope widely.
H, S, V in HSV color space pattern is quantified as 8,3,3 regions by S12 respectively, thus the value of photograph pixel point is quantified as 72 looks; The result quantized by each pixel (H, S, V) of image is (H`, S`, V`), can reduce after 72 looks are quantified as on HSV color space aberration on image ratio on impact and reduce image processing time;
Picture pixels point after quantification is converted to planimetric coordinates by S13, and transformation result is (H``, S``, V``).
The photograph pixel value being converted to planimetric coordinates uses edge detection calculation to go out the variation tendency of X-axis and Y-axis by S14.
Further, obtain two vectors by step S14 and calculate these two vectorial angle theta, whether similarly can be used for judging on the attribute at certain edge.
S15 obtains the microstructure features on photo, and its method is specially,
Picture is cut into several nonoverlapping square microstructure area by S151;
S152 compares the surrounding pixel point in each microstructure area and central pixel point;
The surrounding pixel identical with central pixel point point retains by S153, otherwise deletes;
Turned right by centre in the comparison position, center of microstructure area by S154 successively, under, bottom right moves a pixel, segmentation is re-started to image, then carries out the determining step of (S53);
Reservation pixel after above-mentioned four kinds of blocks cutting computing merges by S155, obtains required microstructure features.
To in each microstructure unit region, around pixel and central pixel point compare S156;
The pixel identical with central pixel point retains by S157, otherwise deletes.
The color data that the feature locations that step S15 obtains by S16 and step S2 obtain combines
The feature that step S16 obtains by S17 uses the proper vector of statistics with histogram picture,
The feature calculation that S171 is obtained by step S6 is published picture as size and is calculated radius and the center of circle of minimum circumscribed circle;
S172 is overlapping with the circumscribed circle center of circle of above-mentioned steps by polar center of circle, and circumscribed circle is divided into the region that several concentric circless form;
Characteristic record corresponding to each region gets up and uses statistics with histogram by S173.
Finally, the picture feature of acquisition vector is compared with the picture feature vector in database, utilizes Euclidean distance to determine the Item Information of captured photo.
Wherein P and Q is respectively the picture of picture in database and shooting, i and j then represents the statistics number in each interval in histogram.
Further, step S4 calculates the length of object and wide after carrying out rim detection to planimetric coordinates, and by the central point of characteristic area and move to photo quantize after central point.
In a three dimensions, if an axle is wherein fixed (as z-axis), through rotating arbitrarily, its parameter may change, but functional value remains unchanged, calculate object length and wide after can draw the center of object, accurately can carry out the acquisition of feature when object different rotation angle to it with this.
Further, in order to improve accuracy rate and the identification range of identification further, except the characteristic obtaining Original Photo sheet contrasting, also comprising and photo eigen flip horizontal, flip vertical and pixel shift acquisition characteristic is contrasted again.
The proper vector obtained stores by S18.
S2 monitors in real time to domestic environment;
Adopt the method for S1 to gather the realtime image data of domestic environment during monitoring, and the environment of data and storage and kinsfolk's feature are compared.
S3 sends alarm signal to information receiving terminal when there is dangerous situation;
Wherein, the people that the dangerous situation described in S3 includes non-family members occurs, the toppling over of target furniture, the falling down and occur the sound that child crys of old man's walking.
Can be judged by setting sound decibel and the threshold value of duration the judgement of child's abnormal conditions; Also can be trained by the data of sound of crying to child and again the sound implementing to obtain be carried out contrast judgement with it.
Further, real time data and the contrast to when height of C.G. storing Data Comparison and comprise profile.
Wherein the calculation procedure of gravity center of human body's height comprises:
1, the center of gravity of head and foot is calculated;
Task image need be divided into head zone and foot areas when calculating head and foot's center of gravity, wherein, described head zone height accounts for 20% of height, and described foot areas height accounts for 33% of height.
Further, the pixel that head center of gravity chooses 65% downwards by the top of described head zone is determined, it is minimum that head center of gravity is defined as this pixel to head each Distance geometry put borderline.
Foot's center of gravity is that the pixel that foot areas bottom upwards chooses 25% is determined.
Preferably, consider that people squats down or other actions and difference when standing, described foot center of gravity is that the pixel that foot areas bottom upwards chooses 12.5% is determined.
2, the leg-of-mutton area that become with foot three-point shape by head and height is calculated;
3, the leg-of-mutton end is calculated by triangle area with high;
The present invention adopts SVM(supportvectormachine) train, preferably adopt Polynomial function to carry out identification, classification.
Further, adopt the method for S1 to carry out feature extraction to image for toppling over of furniture with the monitoring of face in surrounding environment, and carry out contrasting and then judge whether furniture topples over and whether occurred strange face with the proper vector stored.
Further, when family window or balcony have abnormal people turnover also can alert trigger, thus effectively avoid the turnover of burglar or family old man, there is accident in child.
Further, while information receiving terminal sends alarm signal, also real time picture is sent.
Information receiving terminal of the present invention comprises the equipment especially mobile device that mobile phone, computer, panel computer, TV etc. can receive word, pictorial information.
Implement the present invention, there is following beneficial effect:
The present invention adopts sound and image processing techniques to carry out omnibearing monitoring and nurse to domestic environment, the different requirements of modern's life to house security can be met, and carry out data processing and inversion in conjunction with multitude of different ways, guarantee accuracy rate and the validity of monitoring.
Accompanying drawing explanation
Fig. 1 is first embodiment of the invention structural representation;
Fig. 2 is second embodiment of the invention structural representation.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.
As shown in Figure 1, it is some that system of the present invention comprises mobile monitoring terminal, parametric controller and information receiving terminal, and in the present embodiment, information receiving terminal is 2, comprises mobile phone or apparatus such as computer.Described monitor terminal comprises digit camera and sound collector, the preferred intelligent robot of the present embodiment, and described robot carries out image to multiple domestic environment and sound gathers and the data collected are sent to parametric controller; Described parametric controller comprises image processing system and sound processing system, processes the image data set voice data received, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.
Fig. 2 is the another kind of implementation of the present invention, the difference of the implementation shown in itself and Fig. 1 is to adopt fixing monitor terminal to replace mobile monitoring terminal, the corresponding domestic environment of each fixing monitor terminal, domestic environment and fixing monitor terminal respectively have three in the present embodiment.
Embodiment 1
Adopt the present invention can carry out security monitoring to family, prevent burglar from entering.Its main implementation is by gathering and storing the characteristic information of domestic environment and kinsfolk's picture, when monitoring, data processing is carried out to the realtime graphic photographed, and carry out calculating by the characteristic of picture and compare, thus judge whether the people in present monitoring range belongs to stranger, if so, then alarm signal is sent as information receiving terminal.
The principle that realizes of said method is:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
Step S1 comprises,
S11 transfers the picture pixels of shooting to HSV color space pattern by rgb color space pattern, and the formula of conversion is
Wherein
with
fen Do As obtains the most great Zhi With minimum value in RGB Se Cai Kong Inter, adopts HSV can color combining information and textural characteristics, can improve discrimination power and can identification scope widely.
H, S, V in HSV color space pattern is quantified as 8,3,3 regions by S12 respectively, thus the value of photograph pixel point is quantified as 72 looks; The result quantized by each pixel (H, S, V) of image is (H`, S`, V`), can reduce after 72 looks are quantified as on HSV color space aberration on image ratio on impact and reduce image processing time;
Picture pixels point after quantification is converted to planimetric coordinates by S13, and transformation result is (H``, S``, V``), and its method is
The photograph pixel value being converted to planimetric coordinates uses edge detection calculation to go out the variation tendency of X-axis and Y-axis by S14, and the formula of detection is:
；
Whether further, obtain two vectors and calculate these two vectorial angle theta by step S14, can be used for judging on the attribute at certain edge similar, the computing formula of angle theta is:
S15 obtains the microstructure features on photo, and its method is specially,
Picture is cut into several nonoverlapping square microstructure area by S151;
S152 compares the surrounding pixel point in each microstructure area and central pixel point;
The surrounding pixel identical with central pixel point point retains by S153, otherwise deletes;
Turned right by centre in the comparison position, center of microstructure area by S154 successively, under, bottom right moves a pixel, segmentation is re-started to image, then carries out the determining step of (S53);
Reservation pixel after above-mentioned four kinds of blocks cutting computing merges by S155, obtains required microstructure features.
To in each microstructure unit region, around pixel and central pixel point compare S156;
The pixel identical with central pixel point retains by S157, otherwise deletes.
The color data that the feature locations that step S15 obtains by S16 and step S2 obtain combines, and formula is:
Wherein, M (i, j) is architectural feature, and C (i, j) is the feature of HSV color space.
The feature that step S16 obtains by S17 uses the proper vector of statistics with histogram picture,
The feature calculation that S171 is obtained by step S6 is published picture as size and is calculated radius and the center of circle of minimum circumscribed circle;
S172 is overlapping with the circumscribed circle center of circle of above-mentioned steps by polar center of circle, and circumscribed circle is divided into the region that several concentric circless form;
Characteristic record corresponding to each region gets up and uses statistics with histogram by S173.
Finally, the picture feature of acquisition vector is compared with the picture feature vector in database, utilizes Euclidean distance to determine the Item Information of captured photo.
Particularly, be that several are interval by the characteristic quantification obtained, be preferably 12, be divided into several concentric circless from inside to outside, be preferably 3, therefore in preferred version of the present invention, have 36 characteristic areas.
The feature calculation obtained by step S16 is published picture as size and is calculated radius and the center of circle of minimum circumscribed circle, again that polar center of circle is overlapping with the circumscribed circle center of circle of above-mentioned steps, finally by the Feature point correspondence that obtains on polar coordinates, the feature record in each polar coordinates interval statistics is got up and is added up with histogram.
The judgment formula of Euclidean distance is:
Wherein P and Q is respectively the picture of picture in database and shooting, i and j then represents the statistics number in each interval in histogram.
Further, step S4 calculates the length of object and wide after carrying out rim detection to planimetric coordinates, and by the central point of characteristic area and move to photo quantize after central point.
In a three dimensions, if an axle is wherein fixed (as z-axis), through rotating arbitrarily, its parameter may change, but functional value remains unchanged, calculate object length and wide after can draw the center of object, accurately can carry out the acquisition of feature when object different rotation angle to it with this.
Further, in order to improve accuracy rate and the identification range of identification further, except the characteristic obtaining Original Photo sheet contrasting, also comprising and photo eigen flip horizontal, flip vertical and pixel shift acquisition characteristic is contrasted again.
The proper vector obtained stores by S18.
S2 monitors in real time to domestic environment;
Adopt the method for S1 to gather the realtime image data of domestic environment during monitoring, and the environment of data and storage and kinsfolk's feature are compared.
Embodiment 2
Another purposes of the present invention is nursed the old man in solely looking after the house, and give the alarm when Falls Among Old People signal.
Judge that the mode of Falls Among Old People is that when utilizing people to walk, the change of center of gravity judges, triangle core computing method adopted to the computing method of gravity center of human body's height, is specially:
1, the center of gravity of head and foot is calculated;
Task image need be divided into head zone and foot areas when calculating head and foot's center of gravity, wherein, described head zone height accounts for 20% of height, and described foot areas height accounts for 33% of height.
Further, the pixel that head center of gravity chooses 65% downwards by the top of described head zone is determined, it is minimum that head center of gravity is defined as this pixel to head each Distance geometry put borderline.
Foot's center of gravity is that the pixel that foot areas bottom upwards chooses 25% is determined.
Preferably, consider that people squats down or other actions and difference when standing, described foot center of gravity is that the pixel that foot areas bottom upwards chooses 12.5% is determined.
2, the leg-of-mutton area that become with foot three-point shape by head and height is calculated;
3, the leg-of-mutton end is calculated by triangle area with high;
After head and three centers of gravity of both feet are found out, three centers of gravity finding out are utilized to carry out the calculating of Vector triangle, to judge in picture that personage is that to stand be also non-posture of standing, the method judged is that these three focus points are linked to be a triangle, make the center of gravity of head be A, the center of gravity of bipod is B and C, and the limit that angle A is right is a, the limit that angle B is right is b, and the limit that angle C is right is c.After calculating leg-of-mutton three length of side a, b and c with 2 range formulas, formula (1) and (2) are utilized to calculate leg-of-mutton area, calculate height with area and a again, calculate and adopt formula (3), the end BC drawn is the spacing of bipod center of gravity, the height of head center of gravity is h, calculate ratio v that the is high and end again, as formula (4), and then judge whether that the threshold value T exceeding definition is to judge whether people stands, if value is greater than T, be judged to stand, be less than T and be then judged to be non-standing.
（1）
（2）
（3）
（4）
The present invention adopts SVM(supportvectormachine) train, preferably adopt Polynomial function to carry out identification, classification.
The image personage center-of-gravity value of Real-time Obtaining being compared with threshold value T, being greater than T then for standing, be less than T and then stand for non-.
Preferably, described threshold value T is 3 ~ 3.5.
Embodiment 3
Toppling over of the especially large furniture of family furniture often means that unusual condition appears in domestic environment, for the monitoring method reference example 1 of furniture state, the image feature vector of the furniture image feature vector real-time monitored and storage to be contrasted and the angle calculating the two can judge whether furniture topples over.
Preferably, whether can also to lose the furniture of ad-hoc location according to this method and judge, important furniture is extracted image feature vector separately and stores.Carry out additive operation after realtime graphic and original image are carried out binaryzation, the distinguishing characteristics drawn is identical with the proper vector of the important furniture of storage, represents that the furniture of this position is lost, now alert trigger.
Embodiment 4
The sound around monitor terminal can be collected, when the sound collecting child exceedes certain decibel and certain time then gives the alarm by the sound collector of monitor terminal.
Preferably, the sound of alert trigger need be greater than 55 decibels.
Preferably, described monitor terminal utilizes the sonar unit be equipped with, and can move and the photo taking the sound source of sounding is sent to described information receiving terminal to the sound source of alert trigger.
Preferably, when sound is greater than setting decibel value the value that the frequency sent within a period of time is greater than setting also can trigger above-mentioned alarm, as family enter burglar after move the noise that article send frequently.
The above is the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.
Claims (4)
1. a Smart Home method for supervising, is characterized in that, described method comprises:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
S2 adopts monitor terminal to monitor in real time domestic environment, gathers image and sound and the data collected are sent to parametric controller;
S3 parametric controller processes the image data set voice data received, and judges whether to be in an emergency and sends alarm signal to information receiving terminal, sending alarm signal when there is dangerous situation to information receiving terminal;
Wherein, the people that the dangerous situation described in S3 includes non-family members occurs, the toppling over of target furniture, the falling down and occur the sound that child crys of old man's walking;
Step S1 comprises,
S11 transfers the picture pixels of shooting to HSV color space pattern by rgb color space pattern;
H, S, V in HSV color space pattern is quantified as 8,3,3 regions by S12 respectively, thus the value of photograph pixel point is quantified as 72 looks;
Picture pixels point after quantification is converted to planimetric coordinates by S13;
The photograph pixel value being converted to planimetric coordinates uses edge detection calculation to go out the variation tendency of X-axis and Y-axis by S14;
S15 obtains the microstructure features on photo;
The color data that the feature locations that step S15 obtains by S16 and step S12 obtain combines;
The feature that step S16 obtains by S17 uses the proper vector of statistics with histogram picture;
The proper vector obtained stores by S18.
2. method for supervising according to claim 1, is characterized in that, adopts the method for S1 to gather the realtime image data of domestic environment during monitoring, and the environment of data and storage and kinsfolk's feature is compared.
3. method for supervising according to claim 2, is characterized in that, real time data comprises the contrast to when height of C.G. of profile with storing Data Comparison.
4. method for supervising according to claim 1, is characterized in that, while information receiving terminal sends alarm signal, also send real time picture.
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