CN103177256A - Method for identifying display state of traffic signal lamp - Google Patents
Method for identifying display state of traffic signal lamp Download PDFInfo
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- CN103177256A CN103177256A CN2013101118256A CN201310111825A CN103177256A CN 103177256 A CN103177256 A CN 103177256A CN 2013101118256 A CN2013101118256 A CN 2013101118256A CN 201310111825 A CN201310111825 A CN 201310111825A CN 103177256 A CN103177256 A CN 103177256A
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Abstract
The invention discloses a method for identifying a display state of a traffic signal lamp. The method is used for identifying a current photochromic signal of the traffic signal lamp, and is characterized by comprising the following steps of: acquiring an image containing the traffic signal lamp; extracting quasi-rectangular areas, solving the maximum inscribed rectangle, and extracting a quasi-circle area from the maximum inscribed rectangle; solving the minimum circumcircle of the quasi-circle area as a luminous area; selecting only one contained luminous area, wherein the part with the maximum contained luminous area is taken as a candidate rectangular frame; judging a photochromic signal according to the position of the luminous area in the candidate rectangular frame; extracting the quasi-circle area when the quasi-rectangular area is not extracted, solving the minimum circumcircle, and judging the photochromic signal according to the color component value of the candidate luminous area, wherein the part with the maximum area is taken as the candidate luminous area; and outputting the photochromic signal when the accumulative display value of the photochromic signal reaches a preset threshold value.
Description
Technical field
The present invention relates to the recognition methods of a kind of traffic lights show state.
Technical background
According to the national authority department statistics, blind person's sum of China accounts for global 18%, and is nearly 5,000,000, and low eyesight person approximately has more than 600 ten thousand.The growth rate of China blind person quantity is annual more than 40 ten thousand.Solution looks barrier person's safety problem has important practical significance.By utility appliance, the traffic lights show state on road is detected and identifies, the auxiliary person that looks the barrier is gone on a journey safely has vital role.
In recent years, the research of the detection and identification of traffic lights is subject to extensive concern both domestic and external.Traffic lights detection based on visual pattern collection and processing has passive discerning, easy to use with recognition methods, traffic lights be need not to change, to advantages such as other pedestrians do not disturb.At present detection and the recognition methods based on the traffic lights of visual processes mainly contains three kinds: based on the signal lamp detection method of template matches, based on the method for round-shaped feature extraction and the signal lamp detection method of color-based distribution characteristics.The whole bag of tricks all has relative merits, but due to the impact that is subjected to natural lighting variation and road environment factor, and traditional method based on Shape Feature Extraction is strict to the judgement in traffic lights rectangle frame and circular luminous zone, the misclassification rate of signal lamp and leakage knowledge rate are all higher, and optimization and the stability of algorithm all have much room for improvement.
Summary of the invention
The present invention carries out for overcoming the above problems, and purpose is to propose a kind of traffic lights with high accuracy and real-time and detects and recognition methods, and person's safety provides a kind of effectively auxiliary method in order to look the barrier.
In order to reach above purpose, the present invention has adopted following methods.
Obtain the image that a width contains described traffic lights; Extract a slice class rectangular area at least in described image, the imperial palace of every described class rectangular area is connect rectangle as the first rectangle frame, extract the class circle regional in described the first rectangle frame, the minimum circumscribed circle that described class circle is regional is as light-emitting zone, selection contains and only contains described first rectangle frame of the described light-emitting zone of a slice as the second rectangle frame, selection contains described second rectangle frame of described light-emitting zone of area maximum as the candidate rectangle frame, goes out described photochromic signal according to the position judgment of described light-emitting zone in described candidate rectangle frame; When not extracting described class rectangular area in described image, extract a slice class circle zone at least, every described class is justified the minimum circumscribed circle in zone as the first light-emitting zone, described first light-emitting zone of area maximum as candidate's light-emitting zone, is judged described photochromic signal according to the color component value of described candidate's light-emitting zone; During greater than predetermined threshold value, described photochromic signal is converted to voice output when the accumulative total displayed value of described photochromic signal.
The invention effect
The present invention is in the process of extracting traffic lights rectangle frame and circular luminous zone, extract object and be converted to class rectangle and similar round from strict rectangle and circle shape, this leakage of effectively having avoided causing because of the distortion that occurs in the image preprocessing process is known, and has greatly improved detection and the recognition efficiency of traffic lights.
Description of drawings
Fig. 1 is the process flow diagram of traffic lights show state of the present invention recognition methods;
Fig. 2 is the schematic diagram of three rectangle frames in traffic lights rectangle frame of the present invention upper, middle and lower;
Embodiment
Referring to accompanying drawing, traffic lights based on shape and color characteristic involved in the present invention are detected with recognition methods and are elaborated, present embodiment for red light, amber light and green light according to tactic traffic lights from top to bottom.
Fig. 1 is the process flow diagram of traffic lights show state of the present invention recognition methods.
As shown in Figure 1:
Use variscope spare to gather the coloured image at traffic lights crossing of living in.
After a two field picture in reading in the successive frame sequence image, image is intercepted processing, get the first half of image; Coloured image is converted to gray level image; Getting the circular radius windows radius and be 5 carries out medium filtering and eliminates noise; Carry out top cap conversion and remove large tracts of land uniform gray level zone in image; Automatically get threshold value to Image Segmentation Using by grey level histogram; Get structural element radius 8, the zone that extracts is corroded and expansion process, the aperture in the Closed Graph picture.
Extract the class rectangle connected region of rectangular degree r between 0.8 ~ 1.0, wherein rectangular degree r=A/A
r, A is the area of connected region, A
rThe area of the minimum boundary rectangle of connected region, select area between 500 ~ 5000 pixels, length breadth ratio is between 2.8 ~ 3.4 and vertical class rectangular area, long limit.
The number S4 of class rectangular area is extracted in step 4, judgement.
When extracting at least one class rectangular area (being that class rectangle number is not 0), the imperial palace of asking for the class rectangular area of extracting in step 3 connects rectangle, as the first rectangle frame (being candidate's traffic lights rectangle frame), record top left corner apex coordinate and the lower right corner apex coordinate of each the first rectangle frame; Seek the class circle regional in the first rectangle frame, extraction circularity c is the class circle zone between 100 ~ 800 pixels in the connected region between 0.6 ~ 1.0 and area, wherein circularity c=F/F
R, F is the area in class circle zone, F
RBe the area of the regional minimum circumscribed circle of class circle, the minimum circumscribed circle that the class circle is regional is as light-emitting zone.
Selection contains and only contains round first a regional rectangle frame of above-mentioned class as the second rectangle frame, tries to achieve the regional minimum circumscribed circle of class circle as the traffic lights light-emitting zone, records area A c and the centre coordinate (X of minimum circumscribed circle
C, Y
C), select the second rectangle frame of contained light-emitting zone area A c maximum as the rectangle frame (being the candidate rectangle frame) of target traffic lights.
Step 7, signal S7 photochromic according to light-emitting zone location recognition traffic lights:
Candidate's traffic lights are divided into rectangular area, three of upper, middle and lower, represent respectively three kinds of red, yellow, and green color signal lamp residing zone, Fig. 2 is the schematic diagram of three rectangle frames in traffic lights rectangle frame of the present invention upper, middle and lower, as shown in Figure 2: according to candidate's traffic lights rectangle frame top left corner apex a coordinate (row
1, column
1) and summit, lower right corner b coordinate (row
2, column
2) can try to achieve respectively top left corner apex coordinate and lower right corner apex coordinate, the wherein Height=row of three rectangular areas
2-row
1, Width=column
2-colume
1The c point coordinate is (row1+Height/3, colomn2), the d point coordinate is (row1+2*Height/3, column1), the e point coordinate is (row1+Height/3, colomn1), the f point coordinate is (row1+2*Height/3, column2), the regional extent of top rectangle frame is definite by upper left corner coordinate a and lower right corner coordinate c, and the regional extent of middle part rectangle frame is determined by upper left corner coordinate e and lower right corner coordinate f, the regional extent of bottom rectangle frame is determined by upper left corner coordinate d and lower right corner coordinate b, according to luminous border circular areas centre coordinate (X
C, Y
C) and three rectangular area top left corner apex coordinates and lower right corner apex coordinate can judge which rectangular area the luminous border circular areas of candidate's traffic lights is positioned at, judge that namely which kind of color traffic lights are.
Step 8, when the judged result of S4 is when not extracting the class rectangular area in image, extract light-emitting zone S8 in pretreated image:
Through selecting in pretreated image circularity between 0.6 ~ the 1.0 and class circle zone of region area between 100 ~ 800 pixels, try to achieve minimum circumscribed circle as the first border circular areas, records center coordinate and circumscribed circle area, select area maximum in all first border circular areas as candidate's light-emitting zone.
The candidate's light-emitting zone that extracts is carried out color notation conversion space, obtain red color component value R, green component values G, the blue component value B of each pixel of candidate's light-emitting zone, carry out RGB and obtain the chromatic component value H of each pixel of candidate's light-emitting zone to the HIS color notation conversion space, if
H
1And
T
1, judge that candidate's light-emitting zone is green light, if
＜h
2And
T
2, judge that candidate's light-emitting zone is red light, if h
2＜
＜h
1And
＜t
2, judge that candidate's light-emitting zone is amber light, wherein
,
,
And
Respectively the mean value of chromatic component value H, red color component value R, green component values G and the blue component value B of all pixels in the circular luminous zone, h
1And h
2, t
1And t
2The threshold value of determining according to the actual conditions of described camera and described traffic lights, h
1=80, h
2=30, t
1=200, t
2=80; After the judgement signal lamp color.
Step 11, judge whether count value reaches threshold value S11, when count value corresponding to show state do not reach threshold value (present embodiment gets 8), return to S1.
Step 12, when count value corresponding to show state reaches threshold value, the prompting of output respective quadrature ventilating signal lamp show state, corresponding counter O reset, circulation finishes, and enters next circulation.
Being more than a specific embodiment of the present invention, is not to limit usage range of the present invention, and all equivalences of doing according to the content of the present patent application the scope of the claims change and modify, and all should be technology category of the present invention.
Claims (3)
1. photochromic signal recognition methods of traffic lights is used for the current photochromic signal of identification traffic lights, it is characterized in that, comprises the following steps:
Obtain the image that a width contains described traffic lights;
Extract a slice class rectangular area at least in described image, the imperial palace of every described class rectangular area is connect rectangle as the first rectangle frame, extract the class circle regional in described the first rectangle frame, the minimum circumscribed circle that described class circle is regional is as light-emitting zone, selection contains and only contains described first rectangle frame of the described light-emitting zone of a slice as the second rectangle frame, selection contains described second rectangle frame of described light-emitting zone of maximum area as the candidate rectangle frame, goes out described photochromic signal according to the position judgment of described light-emitting zone in described candidate rectangle frame;
When not extracting described class rectangular area in described image, extract a slice class circle zone at least, every described class is justified the minimum circumscribed circle in zone as the first border circular areas, described first border circular areas of area maximum as candidate's light-emitting zone, is judged described photochromic signal according to the color component value of described candidate's light-emitting zone;
When the accumulative total displayed value of described photochromic signal reaches predetermined threshold value, described photochromic signal is converted to voice output.
2. the photochromic signal recognition methods of traffic lights according to claim 1 is characterized in that:
The rectangular degree r of described class rectangular area is between 0.8 ~ 1.0, and area is between 500 ~ 5000 pixels, and length breadth ratio is between 2.8 ~ 3.4.
3. the photochromic signal recognition methods of traffic lights according to claim 1 is characterized in that:
The circularity c in described class circle zone at the connected region between 0.6 ~ 1.0 and area between 100 ~ 800 pixels.
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| CN201310111825.6A CN103177256B (en) | 2013-04-02 | 2013-04-02 | Display state of traffic signal lamp recognition methods |
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| CN103177256B CN103177256B (en) | 2016-12-28 |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103489324A (en) * | 2013-09-22 | 2014-01-01 | 北京联合大学 | Real-time dynamic traffic light detection identification method based on unmanned driving |
| CN104778833A (en) * | 2014-01-10 | 2015-07-15 | 北京信路威科技股份有限公司 | Traffic light recognition method |
| CN105279511A (en) * | 2015-10-20 | 2016-01-27 | 浙江宇视科技有限公司 | Color time varying characteristic-based traffic light relocating method and device |
| CN105407288A (en) * | 2015-12-07 | 2016-03-16 | 哈尔滨工业大学深圳研究生院 | Image collecting method suitable for blind guiding stick system |
| CN105893971A (en) * | 2016-04-01 | 2016-08-24 | 上海理工大学 | Traffic signal lamp recognition method based on Gabor and sparse representation |
| CN106023623A (en) * | 2016-07-28 | 2016-10-12 | 南京理工大学 | Recognition and early warning method of vehicle-borne traffic signal and symbol based on machine vision |
| CN107369242A (en) * | 2017-06-15 | 2017-11-21 | 深圳怡化电脑股份有限公司 | A kind of Paper Currency Identification, device, terminal device and readable storage medium storing program for executing |
| CN107534716A (en) * | 2015-07-08 | 2018-01-02 | 欧姆龙株式会社 | Image processing apparatus and traffic control system and image processing method with the device |
| CN107886033A (en) * | 2016-09-30 | 2018-04-06 | 比亚迪股份有限公司 | Identify the method, apparatus and vehicle of circular traffic lights |
| CN107945552A (en) * | 2017-11-30 | 2018-04-20 | 北京小米移动软件有限公司 | Become method, apparatus and the storage medium that the lamp time is prompted to signal lamp |
| CN109493335A (en) * | 2018-11-13 | 2019-03-19 | 上海烟草集团有限责任公司 | Piece type coefficient characterizing method, system, computer storage medium and the equipment of piece cigarette |
| CN110826497A (en) * | 2019-11-07 | 2020-02-21 | 厦门市美亚柏科信息股份有限公司 | Vehicle weight removing method and device based on minimum distance method and storage medium |
| CN112906471A (en) * | 2021-01-18 | 2021-06-04 | 国汽智控(北京)科技有限公司 | Traffic signal lamp identification method and device |
Families Citing this family (1)
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| CN109044755A (en) * | 2018-07-18 | 2018-12-21 | 钟祥博谦信息科技有限公司 | A kind of intelligent blind guiding system, device and method |
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Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103489324B (en) * | 2013-09-22 | 2015-09-09 | 北京联合大学 | A kind of based on unpiloted real-time dynamic traffic light detection identification method |
| CN103489324A (en) * | 2013-09-22 | 2014-01-01 | 北京联合大学 | Real-time dynamic traffic light detection identification method based on unmanned driving |
| CN104778833A (en) * | 2014-01-10 | 2015-07-15 | 北京信路威科技股份有限公司 | Traffic light recognition method |
| CN104778833B (en) * | 2014-01-10 | 2018-05-08 | 北京信路威科技股份有限公司 | The method for identifying traffic lights |
| CN107534716A (en) * | 2015-07-08 | 2018-01-02 | 欧姆龙株式会社 | Image processing apparatus and traffic control system and image processing method with the device |
| CN105279511A (en) * | 2015-10-20 | 2016-01-27 | 浙江宇视科技有限公司 | Color time varying characteristic-based traffic light relocating method and device |
| CN105279511B (en) * | 2015-10-20 | 2020-04-07 | 浙江宇视科技有限公司 | Traffic signal lamp repositioning method and device based on color time-varying characteristics |
| CN105407288A (en) * | 2015-12-07 | 2016-03-16 | 哈尔滨工业大学深圳研究生院 | Image collecting method suitable for blind guiding stick system |
| CN105893971A (en) * | 2016-04-01 | 2016-08-24 | 上海理工大学 | Traffic signal lamp recognition method based on Gabor and sparse representation |
| CN106023623A (en) * | 2016-07-28 | 2016-10-12 | 南京理工大学 | Recognition and early warning method of vehicle-borne traffic signal and symbol based on machine vision |
| CN107886033A (en) * | 2016-09-30 | 2018-04-06 | 比亚迪股份有限公司 | Identify the method, apparatus and vehicle of circular traffic lights |
| CN107369242A (en) * | 2017-06-15 | 2017-11-21 | 深圳怡化电脑股份有限公司 | A kind of Paper Currency Identification, device, terminal device and readable storage medium storing program for executing |
| CN107945552A (en) * | 2017-11-30 | 2018-04-20 | 北京小米移动软件有限公司 | Become method, apparatus and the storage medium that the lamp time is prompted to signal lamp |
| CN109493335A (en) * | 2018-11-13 | 2019-03-19 | 上海烟草集团有限责任公司 | Piece type coefficient characterizing method, system, computer storage medium and the equipment of piece cigarette |
| CN110826497A (en) * | 2019-11-07 | 2020-02-21 | 厦门市美亚柏科信息股份有限公司 | Vehicle weight removing method and device based on minimum distance method and storage medium |
| CN110826497B (en) * | 2019-11-07 | 2022-12-02 | 厦门市美亚柏科信息股份有限公司 | Vehicle weight removing method and device based on minimum distance method and storage medium |
| CN112906471A (en) * | 2021-01-18 | 2021-06-04 | 国汽智控(北京)科技有限公司 | Traffic signal lamp identification method and device |
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