CN109785641A - A kind of traffic behavior monitoring device and method - Google Patents
A kind of traffic behavior monitoring device and method Download PDFInfo
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- CN109785641A CN109785641A CN201910177204.5A CN201910177204A CN109785641A CN 109785641 A CN109785641 A CN 109785641A CN 201910177204 A CN201910177204 A CN 201910177204A CN 109785641 A CN109785641 A CN 109785641A
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Abstract
The invention discloses a kind of traffic behavior monitoring device and methods, including monitoring host computer, monitoring host computer includes outer housing, outer housing two sides are equipped with alarming horn, outer housing uses moisture-proof dust cover, outer housing front end face is equipped with ccd image sensor, controller is installed inside outer housing, microprocessor is equipped in controller, Image Acquisition optimization module, locating module, alarm module and wireless transport module, ccd image sensor connects microprocessor by Image Acquisition optimization module, locating module, alarm module is all connected with microprocessor, microprocessor connects background monitoring terminal by wireless transport module, Database Unit is set in background monitoring terminal, it further include image characteristics extraction module, image characteristics extraction module connects microprocessor, structure of the invention principle is simple, it can be realized to the fast of traffic violation Speed crawl can be realized real-time overall monitor traffic behavior, improve efficiency and accuracy that traffic violations behavior determines.
Description
Technical field
The present invention relates to traffic behavior monitoring technology field, specially a kind of traffic behavior monitoring device and method.
Background technique
With the development of internet technology, there is Video Supervision Technique.Current traffic video monitoring can be clapped in real time
Traffic information is taken the photograph, by installing camera at crossing, and camera is connected into traffic management department, monitoring is regarded by departmental staff
Frequency is monitored and determines whether that there are unlawful practices.However there is traffic monitoring inefficiency in which.
Summary of the invention
The purpose of the present invention is to provide a kind of traffic behavior monitoring device and methods, to solve to mention in above-mentioned background technique
Out the problem of.
To achieve the above object, the invention provides the following technical scheme: a kind of traffic behavior monitoring device, including monitoring are led
Machine, the monitoring host computer include outer housing, and the outer housing two sides are equipped with alarming horn, and the outer housing is using moisture-proof dust-proof
Shell, the outer housing front end face are equipped with ccd image sensor, install controller, the controller inside the outer housing
Interior to be equipped with microprocessor, Image Acquisition optimization module, locating module, alarm module and wireless transport module, the ccd image passes
Sensor connects microprocessor by Image Acquisition optimization module, and the locating module, alarm module are all connected with microprocessor, described
Microprocessor connects background monitoring terminal by wireless transport module, Database Unit is arranged in the background monitoring terminal, also
Including image characteristics extraction module, described image characteristic extracting module connects microprocessor.
Preferably, monitoring method the following steps are included:
A, ccd image sensor acquire vehicle driving image, the image transmitting of acquisition into Image Acquisition optimization module into
Row optimization；
B, the image of acquisition is sent to characteristics of image and mentioned by the image transmitting after optimization to microprocessor processes, microprocessor
Feature extraction is carried out to image in modulus block；
C, locating module positions the image of candid photograph simultaneously；
D, simultaneously, the image after feature extraction and location information are transmitted to background monitoring terminal by wireless transport module,
Background monitoring terminal is compared the image of acquisition with the image in Database Unit；
If E, monitoring exception, alarm signal is issued immediately, while positioning output is carried out to illegal position.
Preferably, image optimization method is as follows in the step A:
A, image gray processing becomes color image the gray level image of single-channel data, is obtained according to weighted average method
Gray level image；
B, image enhancement removes unwanted texture in image to contour feature in the prominent image of original image transformation data
Feature；
C, image filtering handles image with Sequential filter, then carries out fusion treatment, specific formula is as follows:
T (x, y)=max (ga(x,y),gb(x,y),gc(x,y),gd(x,y))
Wherein, t (x, y) is gray value of the fused image at coordinate points (x, y), ga(x,y)、gb(x,y)、gc(x,
y)、gd(x, y) be respectively it is horizontal, 45 degree, vertically, gray scale of the Sequential filter result figure in 135 degree of directions at coordinate points (x, y)
Value；
D, image binaryzation is chosen the gray level image of 256 brightness degrees by threshold value and obtains reflection image entirety
With the binary image of local feature, bianry image is obtained using based on the adaptive threshold fuzziness of histogram.
Preferably, image characteristic extracting method is as follows in the step B:
A, image to be extracted is pressed into class Haar method texture feature extraction histogram；
B, the central point pixel of extraction image to be detected and its upper and lower, left and right and four angular vertexs are compared acquisition texture
Feature histogram；
C, cascade image to be detected step a and step b, to obtain image texture characteristic.
Preferably, the ccd image sensor model uses TCD132D.
Preferably, the locating module uses GPS positioning chip or Beidou positioning chip.
Preferably, the microprocessor model uses the single-chip microcontroller of model N76E003.
Compared with prior art, the beneficial effects of the present invention are:
(1) structure of the invention principle is simple, can be realized the quick crawl to traffic violation, can be realized complete in real time
Face monitors traffic behavior, improves efficiency and accuracy that traffic violations behavior determines.
(2) the image optimization method treatment effeciency that the present invention uses is high, and picture quality that treated is good, convenient for the height of image
Precision identification.
(3) image characteristic extracting method that the present invention uses can carry out feature extraction to the image of acquisition, further mention
High traffic behavior monitoring efficiency.
Detailed description of the invention
Fig. 1 is schematic structural view of the invention；
Fig. 2 is invention's principle block diagram；
Fig. 3 is flow chart of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Fig. 1-3 is please referred to, the present invention provides a kind of technical solution: a kind of traffic behavior monitoring device, including monitoring host computer,
The monitoring host computer includes outer housing 1, and 1 two sides of outer housing are equipped with alarming horn 2, and the outer housing 1 is using moisture-proof anti-
Dirt shell, 1 front end face of outer housing are equipped with ccd image sensor 3, and controller 4 is installed inside the outer housing 1, described
Microprocessor 5, Image Acquisition optimization module 6, locating module 7, alarm module 8 and wireless transport module 9 are equipped in controller 4,
The ccd image sensor 3 connects microprocessor 5, the locating module 7, alarm module 8 by Image Acquisition optimization module 6
It is all connected with microprocessor 5, the microprocessor 5 connects background monitoring terminal 10, the background monitoring by wireless transport module 9
Database Unit 11 is set in terminal 10, further includes image characteristics extraction module 12, described image characteristic extracting module 12 connects
Microprocessor 5；Wherein, ccd image sensor model uses TCD132D；Locating module is positioned using GPS positioning chip or Beidou
Chip；Microprocessor model uses the single-chip microcontroller of model N76E003, and N76E003 may operate at two kinds of low-power consumption mode-skies
Not busy mode and power-down mode can select which kind of mode operated in by software.When idle mode, chip master clock is closed, but portion
Point functional module is still run.The closing of chip whole clock ensures that chip power-consumption reaches minimum under power-down mode.It is working normally
Under mode, master clock frequency elimination mode also may be selected and work, it is ensured that flexibly used between power consumption and performance.It is high-effect, abundant
Functional module and configuration, N76E003 can flexibly be used for various applications.
Monitoring method of the invention the following steps are included:
A, ccd image sensor acquire vehicle driving image, the image transmitting of acquisition into Image Acquisition optimization module into
Row optimization；
B, the image of acquisition is sent to characteristics of image and mentioned by the image transmitting after optimization to microprocessor processes, microprocessor
Feature extraction is carried out to image in modulus block；
C, locating module positions the image of candid photograph simultaneously；
D, simultaneously, the image after feature extraction and location information are transmitted to background monitoring terminal by wireless transport module,
Background monitoring terminal is compared the image of acquisition with the image in Database Unit；
If E, monitoring exception, alarm signal is issued immediately, while positioning output is carried out to illegal position.The present invention
In, image optimization method is as follows in step A:
A, image gray processing becomes color image the gray level image of single-channel data, is obtained according to weighted average method
Gray level image；
B, image enhancement removes unwanted texture in image to contour feature in the prominent image of original image transformation data
Feature；
C, image filtering handles image with Sequential filter, then carries out fusion treatment, specific formula is as follows:
T (x, y)=max (ga(x,y),gb(x,y),gc(x,y),gd(x,y))
Wherein, t (x, y) is gray value of the fused image at coordinate points (x, y), ga(x,y)、gb(x,y)、gc(x,
y)、gd(x, y) be respectively it is horizontal, 45 degree, vertically, gray scale of the Sequential filter result figure in 135 degree of directions at coordinate points (x, y)
Value；
D, image binaryzation is chosen the gray level image of 256 brightness degrees by threshold value and obtains reflection image entirety
With the binary image of local feature, bianry image is obtained using based on the adaptive threshold fuzziness of histogram.
The image optimization method treatment effeciency that the present invention uses is high, and picture quality that treated is good, convenient for the high-precision of image
Degree identification.
In addition, image characteristic extracting method is as follows in step B in the present invention:
A, image to be extracted is pressed into class Haar method texture feature extraction histogram；
B, the central point pixel of extraction image to be detected and its upper and lower, left and right and four angular vertexs are compared acquisition texture
Feature histogram；
C, cascade image to be detected step a and step b, to obtain image texture characteristic.
The image characteristic extracting method that the present invention uses can carry out feature extraction to the image of acquisition, further improve
Traffic behavior monitoring efficiency.
In conclusion structure of the invention principle is simple, it can be realized the quick crawl to traffic violation, can be realized
Real-time overall monitor traffic behavior improves efficiency and accuracy that traffic violations behavior determines.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (7)
1. a kind of traffic behavior monitoring device, including monitoring host computer, it is characterised in that: the monitoring host computer includes outer housing (1),
Outer housing (1) two sides are equipped with alarming horn (2), and the outer housing (1) uses moisture-proof dust cover, the outer housing
(1) front end face is equipped with ccd image sensor (3), installs controller (4) inside the outer housing (1), the controller (4)
It is interior to be equipped with microprocessor (5), Image Acquisition optimization module (6), locating module (7), alarm module (8) and wireless transport module
(9), the ccd image sensor (3) passes through Image Acquisition optimization module (6) connection microprocessor (5), the locating module
(7), alarm module (8) is all connected with microprocessor (5), and the microprocessor (5) is supervised by wireless transport module (9) connection backstage
Control terminal (10), it further includes image characteristics extraction module that the background monitoring terminal (10) is interior, which to be arranged Database Unit (11),
(12), described image characteristic extracting module (12) connection microprocessor (5).
2. realizing a kind of monitoring method of traffic behavior monitoring device described in claim 1, it is characterised in that: monitoring method packet
Include following steps:
A, ccd image sensor acquires vehicle driving image, and the image transmitting of acquisition carries out excellent into Image Acquisition optimization module
Change；
B, the image of acquisition is sent to image characteristics extraction mould by the image transmitting after optimization to microprocessor processes, microprocessor
Feature extraction is carried out to image in block；
C, locating module positions the image of candid photograph simultaneously；
D, simultaneously, the image after feature extraction and location information are transmitted to background monitoring terminal by wireless transport module, backstage
Monitor terminal is compared the image of acquisition with the image in Database Unit；
If E, monitoring exception, alarm signal is issued immediately, while positioning output is carried out to illegal position.
3. a kind of monitoring method of traffic behavior monitoring device according to claim 2, it is characterised in that: the step A
Middle image optimization method is as follows:
A, image gray processing, becomes color image the gray level image of single-channel data, obtains gray scale according to weighted average method
Image；
B, image enhancement removes unwanted textural characteristics in image to contour feature in the prominent image of original image transformation data；
C, image filtering handles image with Sequential filter, then carries out fusion treatment, specific formula is as follows:
T (x, y)=max (ga(x,y),gb(x,y),gc(x,y),gd(x,y))
Wherein, t (x, y) is gray value of the fused image at coordinate points (x, y), ga(x,y)、gb(x,y)、gc(x,y)、gd
(x, y) be respectively it is horizontal, 45 degree, vertically, gray value of the Sequential filter result figure in 135 degree of directions at coordinate points (x, y)；
D, image binaryzation is chosen the gray level image of 256 brightness degrees by threshold value and obtains reflection image entirety drawn game
The binary image of portion's feature obtains bianry image using based on the adaptive threshold fuzziness of histogram.
4. a kind of monitoring method of traffic behavior monitoring device according to claim 2, it is characterised in that: the step B
Middle image characteristic extracting method is as follows:
A, image to be extracted is pressed into class Haar method texture feature extraction histogram；
B, the central point pixel of extraction image to be detected and its upper and lower, left and right and four angular vertexs are compared acquisition textural characteristics
Histogram；
C, cascade image to be detected step a and step b, to obtain image texture characteristic.
5. a kind of monitoring method of traffic behavior monitoring device according to claim 1, it is characterised in that: the CCD figure
As sensor model number uses TCD132D.
6. a kind of monitoring method of traffic behavior monitoring device according to claim 1, it is characterised in that: the positioning mould
Block uses GPS positioning chip or Beidou positioning chip.
7. a kind of monitoring method of traffic behavior monitoring device according to claim 1, it is characterised in that: the micro process
Type number uses the single-chip microcontroller of model N76E003.
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| US6882470B2 (en) * | 2001-09-28 | 2005-04-19 | Leica Microsystems Wetzlar Gmbh | Microscope having a contrast-increasing image a acquisition apparatus |
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