CN102819728A - Traffic sign detection method based on classification template matching - Google Patents

Traffic sign detection method based on classification template matching Download PDF

Info

Publication number
CN102819728A
CN102819728A CN2012102457741A CN201210245774A CN102819728A CN 102819728 A CN102819728 A CN 102819728A CN 2012102457741 A CN2012102457741 A CN 2012102457741A CN 201210245774 A CN201210245774 A CN 201210245774A CN 102819728 A CN102819728 A CN 102819728A
Authority
CN
China
Prior art keywords
image
traffic sign
template
classification
sign detection
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN2012102457741A
Other languages
Chinese (zh)
Inventor
汤晓磊
刘同林
许朋飞
张典国
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
No 8357 Research Institute of Third Academy of CASIC
Original Assignee
No 8357 Research Institute of Third Academy of CASIC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by No 8357 Research Institute of Third Academy of CASIC filed Critical No 8357 Research Institute of Third Academy of CASIC
Priority to CN2012102457741A priority Critical patent/CN102819728A/en
Publication of CN102819728A publication Critical patent/CN102819728A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Traffic Control Systems (AREA)
  • Image Analysis (AREA)

Abstract

The invention belongs to the technical field of machine vision and image processing and in particular relates to a traffic sign detection method based on classification template matching. The problems that the conventional traffic sign identification method is complex in operation process, low in real-time property and high in light and image quality requirements are solved. The method comprises the following steps of: segmenting areas containing traffic signs in a photographed image according to different color areas, namely classifying the traffic signs according to colors; (2) screening communicating areas in the image through the shape and area characteristics after the color classification, and positioning the sign area; and (3) identifying through a template matching method. The method has high operability and is insensitive to the light change, and when a source image is blurred, a high identification accuracy rate can be guaranteed, and the method is high in real-time property and can be used for an automatic traffic sign detection device on a vehicle.

Description

A kind of method for traffic sign detection based on the classification model coupling
Technical field
The invention belongs to machine vision and technical field of image processing, be specifically related to a kind of method for traffic sign detection based on the classification model coupling.
Background technology
Along with urban transport problems is serious day by day, intelligent transport technology becomes current research focus and development trend.Intelligent transport technology is that the safety traffic problem of traffic jam issue and vehicle provides huge help.Automatic detection recognition technology for traffic sign is a gordian technique of intelligent transportation field.
Current method for traffic sign detection mainly contains through the identification of classification and the identification through the conventional template matching process.Characteristics such as classifying identification method color, shape combine the neural network scheduling algorithm to segment step by step, finally can confirm it is which kind of sign; Traditional template matching method is that subimage is moved and calculate correlativity to find out the maximum zone of correlativity, perhaps in all templates, searching for to find immediate template after the mark region Primary Location in original image.It is better relatively that the method for simple use classification is carried out the Traffic Sign Recognition real-time; But to analyze the nuance of various traffic sign shape colors through the method that classification is discerned; Classify layer by layer according to general character and individual character; Operating process is very complicated, need a large amount of debugging, and recognition effect is often unsatisfactory.Traditional template matching method calculated amount is bigger, and real-time is relatively poor, and is often higher to hardware requirement in actual traffic sign automatic identification equipment.
In addition, current traffic sign recognition method is had relatively high expectations to color and light, when the two changes, can produce considerable influence to detecting identification.When the movement velocity of the relative traffic sign of camera was very fast, image can thicken, and use traditional recognition methods accuracy rate also can reduce greatly this moment.
Summary of the invention
Technical matters to be solved by this invention is existing traffic sign recognition method complicated operating process, real-time is relatively poor and light and picture quality are required height, and a kind of method for traffic sign detection based on the classification model coupling is provided.
The technical scheme that the present invention adopted is:
A kind of method for traffic sign detection based on the classification model coupling comprises the steps:
(1) zone of containing traffic sign in the photographic images is cut apart by regions of different colours, be about to traffic sign and press color classification;
(2) through shape or area features the connected region in the image is screened behind the color classification, locate this mark region;
(3) discern through the method for template matches.
Aforesaid a kind of method for traffic sign detection based on the classification model coupling, wherein: said step (3) specifically is divided into:
(3.1) use dynamic method for normalizing sign image to be normalized to the target image of m * n: to connect rectangle in the middle mark region of construction step (2), and carry out binary conversion treatment through bimodal method; Utilize bianry image further to confirm the boundary rectangle of mark region internal symbol.
(3.2) template matches is calculated.
Aforesaid a kind of method for traffic sign detection based on classification model coupling, wherein: with the image normalization in the symbol circumscribed rectangular region described in the step (3.1) is the image with the template same size; During step (3.2) coupling; With all templates in the respective color classification respectively with normalization after image carry out matching operation, establishing picture size to be matched is J * K, w (s; T) and f (s; T) be respectively certain pixel value of template image and image to be matched, (x, expression formula y) does the response results c of then final related operation
c ( x , y ) = Σ s = 0 K Σ t = 0 J w ( s , t ) f ( s , t )
According to actual conditions set a c (x, threshold value y), if be higher than this threshold value then this image be the traffic sign of corresponding kind.
Aforesaid a kind of method for traffic sign detection based on the classification model coupling; Wherein: the method for normalizing of said step (3.1) is: the wide and height of establishing source images is respectively x, y; The characteristic image resolution of extracting is m * n; Then will source images be divided into m * n zone, it is following that row is cut apart computing formula:
A. as if x%m=0, then each regional every row of source images should contain x/m pixel
B. as if x%m ≠ 0, the every row in preceding x%m zone contains x/m+1 point; The every row in back m-x%m zone contains the point of x/m;
Column split is calculated and row is cut apart calculating in like manner, detects the number of the black pixel point in each zone, if the stain number thinks then that greater than certain fixing empirical value this zone is a black, the target image corresponding point are changed to stain.
Aforesaid a kind of method for traffic sign detection based on the classification model coupling, wherein: when said step (1) is carried out color classification, adopt following steps:
The rgb image is converted into the hsv image, establishes that (r, g b) are red, the green and blue coordinate of a color respectively; If max is equivalent to r, the maximum among g and the b; If min equals r, the reckling among g and the b; Find in the HSV space (h, s, v) value, h ∈ [0,360) be the hue angle of angle, and s, v ∈ [0,1] is saturation degree and brightness, computing formula is:
Figure BSA00000749667200031
s = 0 , if max = 0 max - min max otherwise
v=max
Aforesaid a kind of method for traffic sign detection based on the classification model coupling, wherein: shape facility comprises girth, circularity, inscribed circle radius or complex shape property described in the step (2).
Aforesaid a kind of method for traffic sign detection based on the classification model coupling; Wherein: also comprise the step of extracting template according to the actual traffic sign image: aim at the traffic sign that will extract template with camera; Carry out step (1)~(3) and in image, catch said traffic sign; Observe and confirm to catch the corresponding two-value array of normalized image that obtains in the correct back output step (3), this two-value array file is template.
The invention has the beneficial effects as follows:
(1) the present invention proposes a kind of classification of location earlier; The traffic sign recognition method of identification again, minimizing at double the template matches in expensive source calculate, through classification and location step by step; Pending zone is dwindled; Thereby significantly reduced interfere information, this time domain acceptance of the bid will and background have very high contrast, have improved real-time and accuracy; And this method has stronger operability, and is insensitive to the light variation, when source images is fuzzy, still can guarantee higher recognition accuracy, and real-time is better, can be used for the traffic sign automatic detection device on the vehicle.
(2) the present invention is cut apart through color the sign in the image is classified; Screen the location through characteristics such as shape area; Only in subclass, search for when coupling is calculated, and use less template, these improve the calculated amount of the template matches that has reduced expensive source greatly; Than ordinary traffic sign higher real-time and accuracy are arranged, be suitable for real-time demanding equipment and use.
(3) can set color, brightness and the saturation degree scope of broad at minute time-like; During the location with the shape condition establish a little less than; Much more as far as possible must keep traffic sign information, leave final accurate identification work for template matches and carry out, can adapt to the variation of various light like this; Use bimodal method binaryzation when confirming the symbol area in the traffic sign in addition, adapt to various light and change.Two improvement above comprehensive make the present invention lower to light and picture quality requirement than commonsense method, the environment that equipment in being fit to move and light often change.
(4) improved conventional method for normalizing, to the source images ranks value different with target image, can the dynamic calculation source images how the zoning is the most reasonable.
(5) use a cover simple and reliable template extraction method, easy operating can or be revised ATL according to the different situation increase and decrease.
Description of drawings
Fig. 1 is a kind of classification, location and an identification step block diagram based on the traffic sign in the method for traffic sign detection of classification model coupling provided by the invention;
Fig. 2 is the selected example of mark region;
Fig. 3 is speed limit 40 sign template examples;
Fig. 4 is a right-hand rotation Warning Mark template example.
Embodiment
Below in conjunction with accompanying drawing and embodiment a kind of method for traffic sign detection based on the classification model coupling provided by the invention is introduced:
As shown in Figure 1, a kind of method for traffic sign detection based on the classification model coupling comprises the steps:
(1) regions of different colours of area-of-interest is cut apart, traffic sign is pressed color classification.
Also possibly comprise information such as highway landscape owing to not only comprise traffic sign usually in the photographic images, but effective discernible traffic sign always appears at some zones of photographic images, therefore to the image setting area-of-interest; And sign commonly used can be divided into red prohibitory sign, blue Warning Mark, yellow warning notice and black designation (as removing speed(-)limit sign) etc. by color, can carry out the classification of the first step through color successively.
When carrying out color classification, existing model below normal employing the: YUV model, YIQ model, Lab model etc.For better classification, the present invention preferably uses a kind of fast conversion method.The color of traffic sign is distinguished more obvious in the HSV space, therefore will the rgb image be converted into the hsv image, establishes that (r, g are respectively red, the green and blue coordinates of a color b), and their value is the real number between 0 to 1.If max is equivalent to r, the maximum among g and the b.If min equals the reckling in these values.Find in the HSV space (h, s, v) value, the h ∈ here [0,360) be the hue angle of angle, and s, v ∈ [0,1] is saturation degree and brightness, computing formula is:
Figure BSA00000749667200051
s = 0 , if max = 0 max - min max otherwise
v=max
H is a tone, every kind of all corresponding h value of color; S is a saturation degree, and the gay colours saturation degree is high, and the white saturation degree is near zero; V is brightness, and this value and light intensity relation is big.Pre-service is for the zone of each color of reservation as much as possible, for versicolor h, s, the v interval of all setting broad of cutting apart.
(2) location of traffic sign
Through characteristics such as shape and areas the connected region in the image is screened the location traffic sign behind the color classification.As shown in Figure 1, red and black split image is then searched for the ring shape zone, and blueness is cut apart the circular fill area of picture search, yellow image search delta-shaped region.
The present invention uses the element marking method to carry out the search of connected region, and travels through the zone that all obtain, and judges whether it possibly is traffic sign according to provincial characteristics, if then draw this mark region of boundary rectangle location of this connected region.
Can use following one or more characteristic when confirming shape:
A. area S: area is one of essential characteristic of rendering image, and the area S of image can represent with the number of pixels that is comprised in the same marked region.
B. perimeter L
The perimeter L of image is with representing apart from sum between adjacent two pixels of outer boundary on the image.
C. circularity R o, inscribed circle radius r and complex shape property e
Circularity R oBe used for describing the scenery shape near circular degree, its computing formula does
R o = 4 πS L 2
S is a graphics area in the formula, and L is the figure girth, R oThe scope of value is 0≤R o≤1, R oMore greatly then figure approaches circle more, is example with continuous circle, square, equilateral triangle, calculates their circularity R oFor: circle, R o=1; Square, R o=0.79; Equilateral triangle, R o=0.6.
Inscribed circle radius r representes with following formula:
r = 2 S L
The implication of S and L is the same in the formula.Equally, be that example result of calculation is: circle, r=R (R is a radius of a circle) with three typical row graphs; Square,
Figure BSA00000749667200071
(a is the foursquare length of side); Equilateral triangle,
Figure BSA00000749667200072
(a is the equilateral triangle length of side).
Complex-shaped sex index dispersion index e commonly used representes that its calculating formula is:
e = L 2 S
This formula has been described the girth size of unit area figure, and the e value is big, shows the Zhou Changda of unit area, and promptly figure is discrete, then is complex figure; Otherwise, then be simple graph.The minimum figure of e value is circular.The result of calculation of typical row graph is: circle, e=12.6; Equilateral triangle, e=20.8; Square, e=16.0.
Judge when circular that e is generally 11.6~13.6 and R oBe 0.9~1.1; Needing e when judging triangle is 18.8~22.8 and R oBe 0.5~0.7.
(3) discern through the method for template matches
The first step uses dynamic method for normalizing sign image to be normalized to the target image of m * n.
With blueness right-hand rotation Warning Mark is example, and preceding step has been confirmed the boundary rectangle in traffic sign zone, with its called after zone 1; Shown in Fig. 2 dotted line; This rectangle is scaled, make rectangle become the sign circle in connect rectangle, be called the zone 2; To remove the outer background interference of sign, shown in Fig. 2 solid line.
Image in the zone 2 is carried out binary conversion treatment through bimodal method (also can select other existing binarization methods for use; For example: clustering procedure, process of iteration, P quantile method, big Tianjin method etc.); Because the contrast of image is stronger in this time domain 2; Bimodal method binaryzation can be partitioned into arrow and the background in the traffic sign well, and this method changes insensitive to light.Further confirm the boundary rectangle of symbol through bianry image, like the zone in Fig. 2 dot-and-dash line 3.
With the image normalizations of zone in 3 is the image with the template same size.Can use existing method for normalizing, but, the present invention proposes the method for a kind of dynamic setting normalization unit in order to express image information more accurately.If the wide and height of source images is respectively x, y, the characteristic image resolution that extract is m * n, then will source images be divided into m * n zone, and it is following that row is cut apart computing formula:
A. as if x%m=0, then each regional every row of source images should contain x/m pixel
B. as if x%m ≠ 0, the every row in preceding x%m zone contains x/m+1 point; The every row in back m-x%m zone contains the point of x/m.
Column split is calculated and row is cut apart compute classes seemingly; Original image is similar to average m * n the zone that be divided into the most at last, detects the number of the black pixel point in each zone, if the stain number is greater than certain empirical value of fixing; Think that then this zone is a black, the target image corresponding point are changed to stain.Can be through top processing with the target image of source images normalization m * n.
In second step, carry out template matches and calculate.
With all templates in the respective color classification respectively with normalization after image carry out matching operation, establishing picture size to be matched is J * K, w (s; T) and f (s; T) be respectively certain pixel value of template image and image to be matched, (x, expression formula y) does the response results c of then final related operation
c ( x , y ) = Σ s = 0 K Σ t = 0 J w ( s , t ) f ( s , t )
(x, threshold value y) think that then this image is the traffic sign of corresponding kind if be higher than this threshold value to set a c according to actual conditions.
(4) extract template according to the actual traffic sign image.
Key step is: camera is aimed at the traffic sign that will extract template; Operation (1)~(3) step is caught this traffic sign in image; Observe and confirm to catch the corresponding two-value array of normalized image that obtains in the correct back output (3), this two-value array file is template.The template array with the image format display effect like Fig. 3, shown in 4.

Claims (7)

1. the method for traffic sign detection based on the classification model coupling comprises the steps:
(1) zone of containing traffic sign in the photographic images is cut apart by regions of different colours, be about to traffic sign and press color classification;
(2) through shape or area features the connected region in the image is screened behind the color classification, locate this mark region;
(3) discern through the method for template matches.
2. a kind of method for traffic sign detection according to claim 1 based on the classification model coupling, it is characterized in that: said step (3) specifically is divided into:
(3.1) use dynamic method for normalizing sign image to be normalized to the target image of m * n: to connect rectangle in the middle mark region of construction step (2), and carry out binary conversion treatment through bimodal method; Utilize bianry image further to confirm the boundary rectangle of mark region internal symbol.
(3.2) template matches is calculated.
3. a kind of method for traffic sign detection based on classification model coupling according to claim 2 is characterized in that: with the image normalization in the symbol circumscribed rectangular region described in the step (3.1) for the image of template same size; During step (3.2) coupling; With all templates in the respective color classification respectively with normalization after image carry out matching operation, establishing picture size to be matched is J * K, w (s; T) and f (s; T) be respectively certain pixel value of template image and image to be matched, (x, expression formula y) does the response results c of then final related operation
c ( x , y ) = Σ s = 0 K Σ t = 0 J w ( s , t ) f ( s , t )
According to actual conditions set a c (x, threshold value y), if be higher than this threshold value then this image be the traffic sign of corresponding kind.
4. a kind of method for traffic sign detection according to claim 3 based on the classification model coupling; It is characterized in that: the method for normalizing of said step (3.1) is: the wide and height of establishing source images is respectively x, y; The characteristic image resolution of extracting is m * n; Then will source images be divided into m * n zone, it is following that row is cut apart computing formula:
A. as if x%m=0, then each regional every row of source images should contain x/m pixel
B. as if x%m ≠ 0, the every row in preceding x%m zone contains x/m+1 point; The every row in back m-x%m zone contains the point of x/m;
Column split is calculated and row is cut apart calculating in like manner, detects the number of the black pixel point in each zone, if the stain number thinks then that greater than certain fixing empirical value this zone is a black, the target image corresponding point are changed to stain.
5. a kind of method for traffic sign detection based on the classification model coupling according to claim 1 and 2 is characterized in that: when said step (1) is carried out color classification, adopt following steps:
The rgb image is converted into the hsv image, establishes that (r, g b) are red, the green and blue coordinate of a color respectively; If max is equivalent to r, the maximum among g and the b; If min equals r, the reckling among g and the b; Find in the HSV space (h, s, v) value, h ∈ [0,360) be the hue angle of angle, and s, v ∈ [0,1] is saturation degree and brightness, computing formula is:
s = 0 , if max = 0 max - min max otherwise
v=max
6. a kind of method for traffic sign detection based on the classification model coupling according to claim 1 and 2, it is characterized in that: shape facility comprises girth, circularity, inscribed circle radius or complex shape property described in the step (2).
7. according to the described a kind of method for traffic sign detection of claim 2~6 based on the classification model coupling; It is characterized in that: also comprise the step of extracting template according to the actual traffic sign image: aim at the traffic sign that will extract template with camera; Carry out step (1)~(3) and in image, catch said traffic sign; Observe and confirm to catch the corresponding two-value array of normalized image that obtains in the correct back output step (3), this two-value array file is template.
CN2012102457741A 2012-07-17 2012-07-17 Traffic sign detection method based on classification template matching Pending CN102819728A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2012102457741A CN102819728A (en) 2012-07-17 2012-07-17 Traffic sign detection method based on classification template matching

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2012102457741A CN102819728A (en) 2012-07-17 2012-07-17 Traffic sign detection method based on classification template matching

Publications (1)

Publication Number Publication Date
CN102819728A true CN102819728A (en) 2012-12-12

Family

ID=47303837

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2012102457741A Pending CN102819728A (en) 2012-07-17 2012-07-17 Traffic sign detection method based on classification template matching

Country Status (1)

Country Link
CN (1) CN102819728A (en)

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103390167A (en) * 2013-07-18 2013-11-13 奇瑞汽车股份有限公司 Multi-characteristic layered traffic sign identification method
CN103413124A (en) * 2013-08-19 2013-11-27 中国科学院自动化研究所 Method for detecting round traffic sign
CN104463105A (en) * 2014-11-19 2015-03-25 深圳市腾讯计算机系统有限公司 Guide board recognizing method and device
CN104937637A (en) * 2013-07-31 2015-09-23 Plk科技株式会社 Vehicular image recognition system for display-board recognition
CN105303189A (en) * 2014-07-29 2016-02-03 阿里巴巴集团控股有限公司 Method and device for detecting specific identification image in predetermined area
CN105488160A (en) * 2015-11-30 2016-04-13 北大方正集团有限公司 Picture hitching method and device, manufacturing method of mapping knowledge domain
CN105550632A (en) * 2014-10-23 2016-05-04 现代摩比斯株式会社 Traffic sign recognizing apparatus and operating method thereof
CN106096587A (en) * 2016-06-29 2016-11-09 韦醒妃 There is the vehicle monitoring system of target recognition function
CN106295644A (en) * 2016-08-11 2017-01-04 海信集团有限公司 Symbol Recognition and device
CN106570494A (en) * 2016-11-21 2017-04-19 北京智芯原动科技有限公司 Traffic signal lamp recognition method and device based on convolution neural network
CN107203767A (en) * 2017-05-24 2017-09-26 深圳市神视检验有限公司 A kind of method and device for aiding in realizing automation Non-Destructive Testing
CN107218889A (en) * 2017-05-24 2017-09-29 深圳市神视检验有限公司 A kind of method and device of measurement position
CN109214434A (en) * 2018-08-20 2019-01-15 上海萃舟智能科技有限公司 A kind of method for traffic sign detection and device
CN110414511A (en) * 2019-07-30 2019-11-05 深圳市普渡科技有限公司 Cooperate sign and system
CN110674863A (en) * 2019-09-19 2020-01-10 北京迈格威科技有限公司 Hamming code identification method and device and electronic equipment
CN111178360A (en) * 2019-12-09 2020-05-19 武汉光庭信息技术股份有限公司 Traffic sign detection positioning method and system
CN111723625A (en) * 2019-03-22 2020-09-29 上海海拉电子有限公司 Traffic light image recognition processing method and device, auxiliary traffic system and storage medium
CN114677701A (en) * 2022-03-11 2022-06-28 联宝(合肥)电子科技有限公司 Data identification method, device, equipment and storage medium
CN116524725A (en) * 2023-07-03 2023-08-01 钧捷科技(北京)有限公司 Intelligent driving traffic sign image data identification system
CN117422714A (en) * 2023-12-18 2024-01-19 大陆汽车电子(济南)有限公司 Assembly inspection method, apparatus, and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101404117A (en) * 2008-10-21 2009-04-08 东软集团股份有限公司 Traffic sign recognition method and device
CN101702197A (en) * 2009-10-26 2010-05-05 宁波大学 Method for detecting road traffic signs
WO2011154978A2 (en) * 2010-06-10 2011-12-15 Tata Consultancy Services Limited An illumination invariant and robust apparatus and method for detecting and recognizing various traffic signs
CN202084185U (en) * 2011-06-16 2011-12-21 长安大学 Automatic traffic sign identification device
CN102542260A (en) * 2011-12-30 2012-07-04 中南大学 Method for recognizing road traffic sign for unmanned vehicle

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101404117A (en) * 2008-10-21 2009-04-08 东软集团股份有限公司 Traffic sign recognition method and device
CN101702197A (en) * 2009-10-26 2010-05-05 宁波大学 Method for detecting road traffic signs
WO2011154978A2 (en) * 2010-06-10 2011-12-15 Tata Consultancy Services Limited An illumination invariant and robust apparatus and method for detecting and recognizing various traffic signs
CN202084185U (en) * 2011-06-16 2011-12-21 长安大学 Automatic traffic sign identification device
CN102542260A (en) * 2011-12-30 2012-07-04 中南大学 Method for recognizing road traffic sign for unmanned vehicle

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
李伦波等: "自然场景下交通标志检测与分类算法研究", 《哈尔滨工业大学学报》, vol. 41, no. 11, 30 November 2009 (2009-11-30) *
许少秋: "户外交通标志检测和形状识别", 《中国图象图形学报》, vol. 14, no. 4, 30 April 2009 (2009-04-30), pages 707 - 711 *

Cited By (31)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103390167A (en) * 2013-07-18 2013-11-13 奇瑞汽车股份有限公司 Multi-characteristic layered traffic sign identification method
CN104937637A (en) * 2013-07-31 2015-09-23 Plk科技株式会社 Vehicular image recognition system for display-board recognition
CN103413124A (en) * 2013-08-19 2013-11-27 中国科学院自动化研究所 Method for detecting round traffic sign
CN103413124B (en) * 2013-08-19 2016-09-21 中国科学院自动化研究所 A kind of circular traffic sign detection method
CN105303189A (en) * 2014-07-29 2016-02-03 阿里巴巴集团控股有限公司 Method and device for detecting specific identification image in predetermined area
US10885644B2 (en) 2014-07-29 2021-01-05 Banma Zhixing Network (Hongkong) Co., Limited Detecting specified image identifiers on objects
US10360689B2 (en) 2014-07-29 2019-07-23 Alibaba Group Holding Limited Detecting specified image identifiers on objects
CN105550632A (en) * 2014-10-23 2016-05-04 现代摩比斯株式会社 Traffic sign recognizing apparatus and operating method thereof
CN105550632B (en) * 2014-10-23 2019-02-15 现代摩比斯株式会社 Traffic mark board identification device and its working method
CN104463105B (en) * 2014-11-19 2017-11-03 清华大学 Guideboard recognition methods and device
CN104463105A (en) * 2014-11-19 2015-03-25 深圳市腾讯计算机系统有限公司 Guide board recognizing method and device
CN105488160A (en) * 2015-11-30 2016-04-13 北大方正集团有限公司 Picture hitching method and device, manufacturing method of mapping knowledge domain
CN106096587A (en) * 2016-06-29 2016-11-09 韦醒妃 There is the vehicle monitoring system of target recognition function
CN106295644A (en) * 2016-08-11 2017-01-04 海信集团有限公司 Symbol Recognition and device
CN106295644B (en) * 2016-08-11 2020-06-09 海信集团有限公司 Symbol identification method and device
CN106570494A (en) * 2016-11-21 2017-04-19 北京智芯原动科技有限公司 Traffic signal lamp recognition method and device based on convolution neural network
CN107218889A (en) * 2017-05-24 2017-09-29 深圳市神视检验有限公司 A kind of method and device of measurement position
CN107203767A (en) * 2017-05-24 2017-09-26 深圳市神视检验有限公司 A kind of method and device for aiding in realizing automation Non-Destructive Testing
CN109214434A (en) * 2018-08-20 2019-01-15 上海萃舟智能科技有限公司 A kind of method for traffic sign detection and device
CN111723625A (en) * 2019-03-22 2020-09-29 上海海拉电子有限公司 Traffic light image recognition processing method and device, auxiliary traffic system and storage medium
CN111723625B (en) * 2019-03-22 2023-08-08 上海海拉电子有限公司 Traffic light image recognition processing method and device, auxiliary traffic system and storage medium
CN110414511A (en) * 2019-07-30 2019-11-05 深圳市普渡科技有限公司 Cooperate sign and system
CN110414511B (en) * 2019-07-30 2022-05-03 深圳市普渡科技有限公司 Cooperative sign recognition method and system for robot
CN110674863A (en) * 2019-09-19 2020-01-10 北京迈格威科技有限公司 Hamming code identification method and device and electronic equipment
CN110674863B (en) * 2019-09-19 2022-06-21 北京迈格威科技有限公司 Hamming code identification method and device and electronic equipment
CN111178360A (en) * 2019-12-09 2020-05-19 武汉光庭信息技术股份有限公司 Traffic sign detection positioning method and system
CN114677701A (en) * 2022-03-11 2022-06-28 联宝(合肥)电子科技有限公司 Data identification method, device, equipment and storage medium
CN116524725A (en) * 2023-07-03 2023-08-01 钧捷科技(北京)有限公司 Intelligent driving traffic sign image data identification system
CN116524725B (en) * 2023-07-03 2023-09-01 钧捷科技(北京)有限公司 Intelligent driving traffic sign image data identification system
CN117422714A (en) * 2023-12-18 2024-01-19 大陆汽车电子(济南)有限公司 Assembly inspection method, apparatus, and storage medium
CN117422714B (en) * 2023-12-18 2024-03-29 大陆汽车电子(济南)有限公司 Assembly inspection method, apparatus, and storage medium

Similar Documents

Publication Publication Date Title
CN102819728A (en) Traffic sign detection method based on classification template matching
CN106651872B (en) Pavement crack identification method and system based on Prewitt operator
CN108108761B (en) Rapid traffic signal lamp detection method based on deep feature learning
CN108765443B (en) Sign enhancement processing method for self-adaptive color threshold segmentation
CN105046196B (en) Front truck information of vehicles structuring output method based on concatenated convolutional neutral net
CN104751142B (en) A kind of natural scene Method for text detection based on stroke feature
CN103559507B (en) The method for traffic sign detection being combined based on color with shape facility
CN103824081B (en) Method for detecting rapid robustness traffic signs on outdoor bad illumination condition
CN109726717B (en) Vehicle comprehensive information detection system
CN104408449B (en) Intelligent mobile terminal scene literal processing method
Zhang et al. A multi-feature fusion based traffic light recognition algorithm for intelligent vehicles
CN109215364B (en) Traffic signal recognition method, system, device and storage medium
Le et al. Real time traffic sign detection using color and shape-based features
CN107066972B (en) Natural scene Method for text detection based on multichannel extremal region
CN105354599A (en) Color recognition method based on improved SLIC super-pixel segmentation algorithm
CN105069466A (en) Pedestrian clothing color identification method based on digital image processing
CN103544484A (en) Traffic sign identification method and system based on SURF
CN103544480A (en) Vehicle color recognition method
CN107330365A (en) Traffic sign recognition method based on maximum stable extremal region and SVM
CN104463138A (en) Text positioning method and system based on visual structure attribute
CN110633635A (en) ROI-based traffic sign board real-time detection method and system
Chakraborty et al. Bangladeshi road sign detection based on YCbCr color model and DtBs vector
CN111462140A (en) Real-time image instance segmentation method based on block splicing
CN107392115B (en) Traffic sign identification method based on hierarchical feature extraction
CN115082776A (en) Electric energy meter automatic detection system and method based on image recognition

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C02 Deemed withdrawal of patent application after publication (patent law 2001)
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20121212