CN105868696A - Method and device for detecting multiple lane lines - Google Patents
Method and device for detecting multiple lane lines Download PDFInfo
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Abstract
The invention discloses a method and device for detecting multiple lane lines, and belongs to the field of intelligent cars. The method comprises the steps: obtaining an image of a lane in front of a car through a camera device; converting the lane image into a gray scale image; carrying out the edge enhancement of a lane line region in the gray scale image, and obtaining an edge enhanced image; obtaining a gray scale segmentation threshold value, carrying out the binarization processing of the edge enhanced image according to the gray scale segmentation threshold value, and obtaining a binary image; judging the internal and external edge points of an internal lane line in the binary image; detecting and tracking the internal lane line according to the features of the lane line; detecting and tracking an external lane line in an external lane line detection region based on the internal lane line, wherein the external lane line detection region is a region from an internal left lane line to an internal right lane line. The method can improve the lane detection efficiency.
Description
Technical field
The present invention relates to intelligent vehicle field, particularly to a kind of method and apparatus detecting multilane lane line.
Background technology
Along with the development of automobile industry, intelligent vehicle has progressed into the life of people.Intelligent vehicle is installed
There is intelligence control system, can assist or replace driver to complete to travel, turn to, the vehicle operating such as parking.
Wherein, intelligence lane-change system can provide bigger help when driver wants to overtake other vehicles lane-change.
During vehicle lane-changing, intelligence lane-change system can be according to millimetre-wave radar and camera collection
Information identification front vehicles and lane line information, then judge whether to meet according to vehicle and lane line information and change
Overtaking other vehicles condition in road, then controls vehicle accelerator, and brake, steering complete lane-change of overtaking other vehicles.
During realizing the present invention, inventor finds that prior art at least there is problems in that
Intelligence lane-change system gets the carriageway image of front multilane by photographic head, then straight according to image
Connect and judge whether left and right vehicle wheel side has track, so, if the image definition got is inadequate, be difficult to
Accurately tell lane line, thus detect the inefficient of track.
Summary of the invention
In order to solve problem of the prior art, embodiments provide a kind of multilane lane line of detecting
Method and apparatus.Described technical scheme is as follows:
First aspect, it is provided that a kind of method detecting multilane lane line, described method includes:
The carriageway image of vehicle front is obtained by shooting part；
Described carriageway image is converted into gray level image；
Lane line region in described gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to described intensity slicing threshold value, described edge strengthening image is carried out two-value
Change processes and obtains binary image；
The outer edge point of fast lane line is judged in described binary image；
According to lane line feature detection and follow the tracks of described fast lane line；
Based on described fast lane line, in lane detection region, outside, detect and follow the tracks of kerb lane line,
Wherein, described kerb lane line detection region is inner side left-lane line with left region and inner side right lane line with the right side
Region.
Second aspect, it is provided that a kind of device detecting multilane lane line, described device includes:
Photographing module, for obtaining the carriageway image of vehicle front by shooting part；
Gray processing module, for being converted into gray level image by described carriageway image；
Edge strengthening module, obtains for lane line region in described gray level image carries out edge strengthening process
Edge strengthening image；
Binarization block, is used for obtaining intensity slicing threshold value, according to described intensity slicing threshold value to described edge
Strengthening image carries out binary conversion treatment and obtains binary image；
Edge detection module, for judging the outer edge point of fast lane line in described binary image；
First detection module, is used for according to lane line feature detection and follows the tracks of described fast lane line；
Second detection module, for based on described fast lane line, detects in lane detection region, outside
And follow the tracks of kerb lane line, wherein, described kerb lane line detection region is that inner side left-lane line is with left region
With inner side right lane line with right region.
The technical scheme that the embodiment of the present invention provides has the benefit that
In the embodiment of the present invention, obtained the carriageway image of vehicle front by shooting part；Carriageway image is turned
Turn to gray level image；Lane line region in gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to intensity slicing threshold value, edge strengthening image is carried out binary conversion treatment and obtain two
Value image；The outer edge point of fast lane line is judged in binary image；Examine according to lane line feature
Survey and follow the tracks of fast lane line；Based on fast lane line, detect and follow the tracks of in lane detection region, outside
Kerb lane line.So, when detecting the lane line of multilane, it is possible to use lane detection algorithm is internal
The lane line of track, side and kerb lane detects respectively, can relatively accurately detect the car of multilane
Diatom, such that it is able to improve the efficiency in detection track.
Accompanying drawing explanation
For the technical scheme being illustrated more clearly that in the embodiment of the present invention, institute in embodiment being described below
The accompanying drawing used is needed to be briefly described, it should be apparent that, the accompanying drawing in describing below is only the present invention
Some embodiments, for those of ordinary skill in the art, on the premise of not paying creative work,
Other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is a kind of method flow diagram detecting multilane lane line that the embodiment of the present invention provides；
Fig. 2 is the general flow chart of a kind of multilane lane detection that the embodiment of the present invention provides；
Fig. 3 is the schematic diagram of a kind of lane detection process that the embodiment of the present invention provides；
Fig. 4 is the schematic diagram of a kind of each lane line definition that the embodiment of the present invention provides；
Fig. 5 is a kind of apparatus structure schematic diagram detecting multilane lane line that the embodiment of the present invention provides；
Fig. 6 is a kind of apparatus structure schematic diagram detecting multilane lane line that the embodiment of the present invention provides；
Fig. 7 is a kind of apparatus structure schematic diagram detecting multilane lane line that the embodiment of the present invention provides；
Fig. 8 is the structural representation of a kind of mobile unit that the embodiment of the present invention provides.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing to the present invention
Embodiment is described in further detail.
Embodiments providing a kind of method detecting multilane lane line, the executive agent of the method can
To be mobile unit, wherein, mobile unit can be mounted in the smart machine on automobile, the most vehicle-mounted meter
Calculation machines etc., this mobile unit can include processor, memorizer, shooting part etc., and processor may be used for
Process during detection lane line, memorizer may be used for storing in processing procedure the data that need with
And the data produced, shooting part can be used to obtain the image of vehicle periphery, all right in this mobile unit
Being provided with the input-output equipment such as screen, screen is displayed for the image of shooting part shooting, this screen
It can be touch control screen.Fig. 2 is Multi-lane Lines Detection general flow chart in this programme.
Below in conjunction with detailed description of the invention, the handling process shown in Fig. 1 is described in detail, content
Can be such that
Step 101, obtains the carriageway image of vehicle front by shooting part.
In force, vehicle is during certain lanes along multilane, and mobile unit may be at
The state of continuous firing, the shooting part in mobile unit can persistently shoot the car of the multilane of vehicle front
Road image.Carriageway image can be divided into upper and lower two parts, and upper part is mainly the image of sky, lower part
For the situation on road surface, upper and lower two parts are with horizon as separation.In the present invention detects the method for lane line,
Lower part image is mainly processed by mobile unit, thus according to lower part image detection vehicle front
Lane line.Wherein, shooting part can be the colour imagery shot of 1280*960 size, and input frame is 30
Frame is per second.
Step 102, is converted into gray level image by carriageway image.
In force, after mobile unit gets carriageway image by shooting part, can be by colored car
Road image carries out gray processing process and obtains gray level image.The color of each pixel in coloured image have R, G,
Tri-components of B determine, and each component has 255 intermediate values desirable, and such a pixel can have more than 1600
The excursion of the color of ten thousand (255*255*255).And gray level image is that tri-components of R, G, B are identical
A kind of special coloured image, the excursion of one pixel is 255 kinds, so in digital picture
The image of various forms first can be transformed into gray level image so that the amount of calculation of follow-up image becomes by process
Few.The description of gray level image still reflect as coloured image entire image entirety and local
Colourity and the distribution of brightness degree and feature, especially in the process of detection lane line, use gray level image
Substantial amounts of noise spot can be removed, make lane line be more easy to be detected.
Step 103, carries out edge strengthening process and obtains edge strengthening image lane line region in gray level image.
In force, after carriageway image is converted into gray level image, can be to the lower half region of gray level image
Carry out edge enhancing, the edge details part in gray level image to be highlighted.In view of lane detection
Real-time, the sobel algorithm in edge detection method based on first differential can be used to carry out edge strengthening
Process.Concrete process can be: first obtains the gray value of each pixel in gray level image, then for often
Individual pixel, can be in the field of 3*3 of point centered by it in calculated level direction and vertical direction
Partial derivative, and then obtain weights coefficient convolution mask.Afterwards, can be by each pixel in former gray level image
Pixel value and this weights multiplication, obtain the pixel value of each pixel after edge strengthening.Concrete,
For carriageway image, the left and right sides of lane line can be highlighted by edge strengthening, i.e. lane line is left
The gray value of right both sides of the edge is higher than the gray value in other region.
Step 104, obtains intensity slicing threshold value, according to intensity slicing threshold value, edge strengthening image is carried out two-value
Change processes and obtains binary image.
In force, after in a step 102 carriageway image being converted into gray level image, gray-scale map can be obtained
As the pixel value of each pixel in the latter half, calculate the gray average of the latter half often row pixel afterwards,
And obtain the gray scale maximum often gone, and then can be according to the gray average of the often row pixel obtained and gray scale
Maximum determines the intensity slicing threshold value that often row pixel is corresponding, concrete, a kind of feasible intensity slicing threshold
Value computing formula is: intensity slicing threshold value=(gray scale maximum gray average) * predetermined coefficient+gray average,
Wherein, predetermined coefficient can be that technical staff is according to historical experience sets itself.
After determining intensity slicing threshold value, according to this intensity slicing threshold value, edge strengthening image can be carried out
Binary conversion treatment, i.e. when in gray level image the gray value of certain pixel more than the intensity slicing threshold of its corresponding row
During value, the gray value of this point is adjusted to high grade grey level (being 255 grades), on the contrary, when in gray level image
When the gray value of certain pixel is less than the intensity slicing threshold value of its corresponding row, the gray value of this point is set to
Minimum gray level (is 0 grade), as such, it is possible to by the gray value of all pixels in edge strengthening image
All it is converted into 0 or 255.Afterwards, according to the basic feature of carriageway image, car in edge strengthening image
The gray value of the pixel at the edge of diatom is 255, then the pixel that gray value is 255 can be set to track
Line candidate point.
Optionally, it is contemplated that in real scene, the gray value of left and right sides lane line difference, accordingly,
The process of step 104 can be such that the intensity slicing threshold value obtaining left and right vehicle wheel both sides respectively, and edge is strong
Changing image division is left and right two parts；Intensity slicing threshold value according to the left and right sides, respectively to edge strengthening figure
Left and right two parts of picture carry out binary conversion treatment and obtain binary image.
In force, after in a step 102 carriageway image being converted into gray level image, gray-scale map can be obtained
As the pixel value of each pixel in the latter half, afterwards the latter half is again split into left and right two halves part.It
After can calculate the gray average of lower left half often row pixel, and obtain the gray scale maximum often gone, enter
And can determine that often row pixel is corresponding according to the gray average of the often row pixel obtained with gray scale maximum
Intensity slicing threshold value, concrete, a kind of feasible intensity slicing threshold calculations formula is: intensity slicing threshold value=
(gray scale maximum gray average) * predetermined coefficient+gray average, wherein, predetermined coefficient can be technology
Personnel are according to historical experience sets itself.Based on same process, the gray scale of vehicle right side can be calculated
Segmentation threshold.
After determining intensity slicing threshold value, can be according to the intensity slicing threshold value of the left and right sides respectively to edge
Left and right two parts of strengthening image carry out binary conversion treatment, i.e. when the gray value of certain pixel in gray level image
During more than the intensity slicing threshold value of its corresponding row, the gray value of this point is adjusted to high grade grey level and (is 255
Level), on the contrary, when in gray level image, the gray value of certain pixel is less than the intensity slicing threshold value of its corresponding row,
The gray value of this point is set to minimum gray level (being 0 grade), as such, it is possible to by edge strengthening image
The gray value of all pixels be all converted into 0 or 255.Afterwards, according to the basic feature of carriageway image,
In edge strengthening image, the gray value of the pixel at the edge of lane line is 255, then can be by gray value
The pixel of 255 is set to lane line candidate point.
Step 105, judges the outer edge of fast lane line in binary image.
Wherein, fast lane line can be the lane line of the left and right sides nearest apart from vehicle axis.
In force, after obtaining binary image, can be according to the width information of lane line, in two-value
Change and image extracts lane line inside edge point.Concrete, binary image can be progressively scanned, obtain every
The gray value of row pixel.If detecting that the gray value of certain pixel is 255, then by this pixel for the first time
Be set to starting point, the rule of conversion of the follow-up gray value persistently judging this row later pixel point.If risen
After initial point, the Changing Pattern of the gray value of each pixel is the gray scale occurring a number of pixel the most continuously
Value is 255, then occurs that the gray value of a number of pixel is 0 continuously, occurs certain more continuously
The gray value of the pixel of quantity is 255, then can be determined that the pixel that gray value is 255 of appearance continuously is
The outer edge point of lane line.It addition, the pixel that a number of gray value is 255 occurs in second time
After, the quantity that the pixel that gray value is 0 occurs continuously after can adding up, and then may determine that these
Length shared by pixel, if this length is more than certain length threshold, then it is believed that above-mentioned lane line
Outer edge point correct judgment.Herein, length threshold can be set according to practical experience by technical staff.
Further, since the width of lane line draws near and gradually broadens in image, the picture that corresponding lane line is occupied
The number of vegetarian refreshments also draws near and is gradually increased, then can be pre-recorded and store every runway live width in image
The number of the pixel that degree is corresponding.
Step 106, according to lane line feature detection and follow the tracks of fast lane line.
In force, after the candidate point of the outer edge point and lane line that determine lane line, according to car
Diatom is generally the feature of continuous linear, it is possible to use hough converter technique carries out straight line to these pixels
Matching, is defined as the fast lane line detected afterwards by the straight line fitted to.Meanwhile, can be according to track
Width between the lane line of the left and right sides, judges that the fast lane line of detection is the most correct.Meanwhile, permissible
Whether the extended line of detection lane line meets at a bit, such that it is able to reject invalid lane line.
During vehicle travels, can persistently obtain vehicle image, driving diatom detection of going forward side by side, the most also
Can be tracked the line of vehicles detected, concrete mode can be to obtain the present count before current time
Mesh lane detection result, it is judged that the amplitude of variation of lane line, rejects the track that some amplitudes of variation are bigger
Line, can ensure that the accuracy of lane detection afterwards, and auxiliary driver drives vehicle in track.
Fig. 3 is the rough schematic of lane detection handling process.
Step 107, based on fast lane line, detects in lane detection region, outside and follows the tracks of kerb lane
Line, wherein, kerb lane line detection region is inner side left-lane line with left region and inner side right lane line with the right side
Region.
In force, after having detected fast lane line, can be by inner side left-lane line with left region and inner side
Right lane line is defined as kerb lane line detection region with right region, and then can be in lane detection district, outside
Detect whether in territory to there is lane line.Fig. 4 is that each lane line defines schematic diagram.If there is lane line, then
Can use step 105 and 106 method detect and follow the tracks of kerb lane line.If it does not exist, then do not enter
Row subsequent detection works.It is noted that this programme can detect track, vehicle place, and with vehicle
Centered by the lane line in track, the left and right sides, and the lane line in track, more lateral is not detected.It addition,
Owing to, compared with fast lane line, the pixel that kerb lane line width occupies in the picture is relatively fewer, sentencing
During the outer edge of disconnected kerb lane line, need to judge according to the width of kerb lane line.
Optionally, it is to avoid fast lane line affects the detection of kerb lane line, can be at outside lane detection
Region is removed near the part of fast lane line, accordingly, the process of step 107 can be such that by from
The region of fast lane alignment external expansion preset width is as outer lane detection region, lane detection outside
Region is detected kerb lane line.
In force, after having detected fast lane line, river bend in having during avoiding the detection of kerb lane line
Measuring car diatom disturbs, and outward expansion one fixed width can examine as kerb lane line at fast lane line position
Survey original position, i.e. can just from the region of fast lane alignment external expansion preset width as outer track
Line detection region, and then can detect whether to there is lane line in lane detection region, outside.
Optionally, after detecting kerb lane line, have and multiple judge kerb lane line whether effective manner,
Two kinds of feasible modes given below:
Mode one: if the distance of kerb lane line and fast lane line is less than predetermined threshold value, then judge outside
Lane line is invalid lane line.
In force, after having detected kerb lane line, can survey according to the testing result of fast lane line
The distance of the kerb lane linear distance fast lane line that amount detection obtains, if distance between the two is less than car
The half of road width, then judge that the kerb lane line detected is invalid lane line, it is impossible to as lane line with
Track candidate line, on the contrary then can enter lane line follow the tracks of candidate's sequence using kerb lane line as effective wagon diatom
Row.Further, if there is the outer lane line of left and right sides simultaneously, then can according to two kerb lane lines it
Between the effectiveness of Distance Judgment kerb lane line.
Mode two: if in multiple carriageway images continuously, kerb lane line and the base intersection point of carriageway image
Within being in preset range, then judge that kerb lane line is effective wagon diatom.
In force, kerb lane line can be judged whether according to kerb lane line and carriageway image base intersection point
Effectively.If in multiple carriageway images being continuously shot, the intersection point on kerb lane line and base is at certain model
Enclose interior variation, then it is believed that this kerb lane line is effective wagon diatom.
In the embodiment of the present invention, obtained the carriageway image of vehicle front by shooting part；Carriageway image is turned
Turn to gray level image；Lane line region in gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to intensity slicing threshold value, edge strengthening image is carried out binary conversion treatment and obtain two
Value image；The outer edge point of fast lane line is judged in binary image；Examine according to lane line feature
Survey and follow the tracks of fast lane line；Based on fast lane line, detect and follow the tracks of in lane detection region, outside
Kerb lane line.So, when detecting the lane line of multilane, it is possible to use lane detection algorithm is internal
The lane line of track, side and kerb lane detects respectively, can relatively accurately detect the car of multilane
Diatom, such that it is able to improve the efficiency in detection track.
Based on identical technology design, the embodiment of the present invention additionally provides a kind of dress detecting multilane lane line
Put, as it is shown in figure 5, described device includes:
Photographing module 501, for obtaining the carriageway image of vehicle front by shooting part；
Gray processing module 502, for being converted into gray level image by described carriageway image；
Edge strengthening module 503, processes for lane line region in described gray level image is carried out edge strengthening
To edge strengthening image；
Binarization block 504, is used for obtaining intensity slicing threshold value, according to described intensity slicing threshold value to described limit
Edge strengthening image carries out binary conversion treatment and obtains binary image；
Edge detection module 505, for judging the outer edge of fast lane line in described binary image
Point；
First detection module 506, is used for according to lane line feature detection and follows the tracks of described fast lane line；
Second detection module 507, for based on described fast lane line, examines in lane detection region, outside
Surveying and follow the tracks of kerb lane line, wherein, described kerb lane line detection region is left-lane Xian Yizuo district, inner side
Territory and inner side right lane line are with right region.
Optionally, described binarization block 504, it is used for:
Obtain the intensity slicing threshold value of described left and right vehicle wheel both sides respectively, by described edge strengthening image division be
Left and right two parts；
Intensity slicing threshold value according to the described left and right sides, respectively two, the left and right to described edge strengthening image
Point carrying out binary conversion treatment obtains binary image.
Optionally, described second detection module 507, it is used for:
Using the region from described fast lane alignment external expansion preset width as outer lane detection region,
Kerb lane line is detected and follows the tracks of in described outer lane detection region.
Optionally, as shown in Figure 6, described device also includes:
First judge module 508, if the distance for described kerb lane line with described fast lane line is less than
Predetermined threshold value, then judge that described kerb lane line is invalid lane line.
Optionally, as it is shown in fig. 7, described device also includes:
Second judge module 509, if be used in multiple carriageway images continuously, described kerb lane line and institute
State within the base intersection point of carriageway image is in preset range, then judge that described kerb lane line is effective wagon
Diatom.
In the embodiment of the present invention, obtained the carriageway image of vehicle front by shooting part；Carriageway image is turned
Turn to gray level image；Lane line region in gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to intensity slicing threshold value, edge strengthening image is carried out binary conversion treatment and obtain two
Value image；The outer edge point of fast lane line is judged in binary image；Examine according to lane line feature
Survey and follow the tracks of fast lane line；Based on fast lane line, detect and follow the tracks of in lane detection region, outside
Kerb lane line.So, when detecting the lane line of multilane, it is possible to use lane detection algorithm is internal
The lane line of track, side and kerb lane detects respectively, can relatively accurately detect the car of multilane
Diatom, such that it is able to improve the efficiency in detection track.
It should be understood that the device detecting multilane lane line that above-described embodiment provides is in multilane track
During line, only it is illustrated with the division of above-mentioned each functional module, in actual application, can be as required
And above-mentioned functions distribution is completed by different functional modules, will the internal structure of device be divided into different
Functional module, to complete all or part of function described above.It addition, the inspection that above-described embodiment provides
The embodiment of the method for the device and detection multilane lane line of surveying multilane lane line belongs to same design, its tool
Body realizes process and refers to embodiment of the method, repeats no more here.
Refer to Fig. 8, it illustrates the structural representation of mobile unit involved by the embodiment of the present invention, this car
Load equipment can be smart mobile phone, vehicle-mounted terminal equipment etc., may be used for implementing offer in above-described embodiment
The method of detection multilane lane line.Specifically:
Mobile unit 800 can include RF (Radio Frequency, radio frequency) circuit 810, include one
Individual or the memorizer 820 of more than one computer-readable recording medium, input block 830, display unit 840,
DSRC module 850, voicefrequency circuit 860, include one or more than one process core processor 870,
GPS module 880 (Global Positioning System, global positioning system), and the portion such as power supply 890
Part.It will be understood by those skilled in the art that the mobile unit structure shown in Fig. 8 is not intended that to set vehicle-mounted
Standby restriction, can include that ratio illustrates more or less of parts, or combine some parts, or different
Parts arrange.Wherein:
During RF circuit 810 can be used for receiving and sending messages, the reception of signal and transmission.Generally, RF circuit
810 include but not limited to antenna, at least one amplifier, tuner, one or more agitator, transmitting-receiving letter
Machine, bonder, LNA (Low Noise Amplifier, low-noise amplifier), duplexer etc..Additionally,
RF circuit 810 can also be communicated with network and other equipment by radio communication.Described radio communication can make
By arbitrary communication standard or agreement, include but not limited to GSM (Global System of Mobile
Communication, global system for mobile communications), GPRS (General Packet Radio Service, general
Packet wireless service), CDMA (Code Division Multiple Access, CDMA),
WCDMA (Wideband Code Division Multiple Access, WCDMA) etc..
Memorizer 820 can be used for storing software program and module, and processor 870 is stored in by operation
The software program of reservoir 820 and module, thus perform the application of various function and data process.Memorizer
820 can mainly include store program area and storage data field, wherein, storage program area can store operating system,
Application program (such as sound-playing function, image player function etc.) etc. needed at least one function；Deposit
Storage data field can store data (the such as voice data, phone that the use according to mobile unit 800 is created
This etc.) etc..Additionally, memorizer 820 can include high-speed random access memory, it is also possible to include non-easily
The property lost memorizer, for example, at least one disk memory, flush memory device or the storage of other volatile solid-state
Device.Correspondingly, memorizer 820 can also include Memory Controller, to provide processor 870 and defeated
Enter the unit 830 access to memorizer 820.
Input block 830 can be used for receive input numeral or character information, and produce with user setup with
And function controls relevant keyboard, mouse, action bars, optics or the input of trace ball signal.Specifically,
Input block 830 can include Touch sensitive surface 831 and other input equipments 832.Touch sensitive surface 831, also referred to as
For touching display screen or Trackpad, can collect user thereon or neighbouring touch operation (such as user makes
With any applicable object such as finger, stylus or adnexa on Touch sensitive surface 831 or attached at Touch sensitive surface 831
Near operation), and drive corresponding attachment means according to formula set in advance.Optionally, Touch sensitive surface 831
Touch detecting apparatus and two parts of touch controller can be included.Wherein, touch detecting apparatus detects user's
Touch orientation, and detect the signal that touch operation brings, transmit a signal to touch controller；Touch control
Device receives touch information from touch detecting apparatus, and is converted into contact coordinate, then gives processor 870,
And order that processor 870 sends can be received and performed.Furthermore, it is possible to use resistance-type, condenser type,
The polytype such as infrared ray and surface acoustic wave realizes Touch sensitive surface 831.Except Touch sensitive surface 831, input is single
Unit 830 can also include other input equipments 832.Specifically, other input equipments 832 can include but not
It is limited to physical keyboard, function key (such as volume control button, switch key etc.), trace ball, mouse, behaviour
Make one or more in bar etc..
Display unit 840 can be used for the information that inputted by user of display or the information being supplied to user and vehicle-mounted
The various graphical user interface of equipment 800, these graphical user interface can by figure, text, icon,
Video and its combination in any are constituted.Display unit 840 can include display floater 841, optionally, can adopt
With LCD (Liquid Crystal Display, liquid crystal display), OLED (Organic Light-Emitting Diode,
Organic Light Emitting Diode) etc. form configure display floater 841.Further, Touch sensitive surface 831 can cover
Display floater 841, when Touch sensitive surface 831 detects thereon or after neighbouring touch operation, sends process to
Device 870 is to determine the type of touch event, with preprocessor 870 according to the type of touch event at display surface
Corresponding visual output is provided on plate 841.Although in fig. 8, Touch sensitive surface 831 and display floater 841
It is to realize input and input function as two independent parts, but in some embodiments it is possible to will
Touch sensitive surface 831 is integrated with display floater 841 and realizes input and output function.
Voicefrequency circuit 860, speaker 861, microphone 862 can provide between user and mobile unit 800
Audio interface.The signal of telecommunication after the voice data conversion that voicefrequency circuit 860 can will receive, is transferred to raise one's voice
Device 861, is converted to acoustical signal output by speaker 861；On the other hand, the sound that microphone 862 will be collected
Tone signal is converted to the signal of telecommunication, voicefrequency circuit 860 be converted to voice data after receiving, then by voice data
After output processor 870 processes, through RF circuit 880 to be sent to such as another mobile unit, or by sound
Frequency is according to exporting to memorizer 820 to process further.Voicefrequency circuit 860 is also possible that earphone jack,
To provide the communication of peripheral hardware earphone and mobile unit 800.
Processor 870 is the control centre of mobile unit 800, utilizes various interface and the whole hands of connection
The various piece of machine, is stored in the software program in memorizer 820 and/or module by running or performing, with
And call the data being stored in memorizer 820, perform the various functions of mobile unit 800 and process data,
Thus mobile phone is carried out integral monitoring.Optionally, processor 870 can include one or more process core；
Preferably, processor 870 can integrated application processor and modem processor, wherein, application processor
Mainly processing operating system, user interface and application program etc., modem processor mainly processes channel radio
Letter.It is understood that above-mentioned modem processor can not also be integrated in processor 870.
Mobile unit 800 also includes the power supply 890 such as battery powered to all parts, it is preferred that power supply
Can be logically contiguous with processor 870 by power-supply management system, thus realize pipe by power-supply management system
The functions such as reason charging, electric discharge and power managed.Power supply 890 can also include one or more
Direct current or alternating current power supply, recharging system, power failure detection circuit, power supply changeover device or inverter,
The random component such as power supply status indicator.
DSRC module 850 may be used for communicating with instruction equipment.
Mobile unit 800 also includes GPS (Global Positioning System, global positioning system) module
880, may be used for detecting the positional information being presently in.
Although not shown, mobile unit 800 can also include photographic head, bluetooth module etc., the most superfluous at this
State.The most in the present embodiment, the display unit of mobile unit 800 is touch-screen display, mobile unit
800 also include memorizer, and one or more than one program, one of them or more than one journey
Sequence is stored in memorizer, and is configured to be performed to state one or one by one or more than one processor
Individual procedure above comprises the instruction for carrying out following operation:
The carriageway image of vehicle front is obtained by shooting part；
Described carriageway image is converted into gray level image；
Lane line region in described gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to described intensity slicing threshold value, described edge strengthening image is carried out two-value
Change processes and obtains binary image；
The outer edge point of fast lane line is judged in described binary image；
According to lane line feature detection and follow the tracks of described fast lane line；
Based on described fast lane line, in lane detection region, outside, detect and follow the tracks of kerb lane line,
Wherein, described kerb lane line detection region is inner side left-lane line with left region and inner side right lane line with the right side
Region.
Optionally, described acquisition intensity slicing threshold value, according to described intensity slicing threshold value to described edge strengthening
Image carries out binary conversion treatment and obtains binary image, including:
Obtain the intensity slicing threshold value of described left and right vehicle wheel both sides respectively, by described edge strengthening image division be
Left and right two parts；
Intensity slicing threshold value according to the described left and right sides, respectively two, the left and right to described edge strengthening image
Point carrying out binary conversion treatment obtains binary image.
Optionally, described in lane detection region, outside, detect and follow the tracks of kerb lane line, including:
Using the region from described fast lane alignment external expansion preset width as outer lane detection region,
Kerb lane line is detected and follows the tracks of in described outer lane detection region.
Optionally, described method also includes:
If described kerb lane line is less than predetermined threshold value with the distance of described fast lane line, then judge described
Kerb lane line is invalid lane line.
Optionally, described method also includes:
If in multiple carriageway images continuously, described kerb lane line and the base intersection point of described carriageway image
Within being in preset range, then judge that described kerb lane line is effective wagon diatom.
In the embodiment of the present invention, obtained the carriageway image of vehicle front by shooting part；Carriageway image is turned
Turn to gray level image；Lane line region in gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to intensity slicing threshold value, edge strengthening image is carried out binary conversion treatment and obtain two
Value image；The outer edge point of fast lane line is judged in binary image；Examine according to lane line feature
Survey and follow the tracks of fast lane line；Based on fast lane line, detect and follow the tracks of in lane detection region, outside
Kerb lane line.So, when detecting the lane line of multilane, it is possible to use lane detection algorithm is internal
The lane line of track, side and kerb lane detects respectively, can relatively accurately detect the car of multilane
Diatom, such that it is able to improve the efficiency in detection track.
One of ordinary skill in the art will appreciate that all or part of step realizing above-described embodiment can be passed through
Hardware completes, it is also possible to instructing relevant hardware by program and complete, described program can be stored in
In a kind of computer-readable recording medium, storage medium mentioned above can be read only memory, disk or
CD etc..
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all the present invention's
Within spirit and principle, any modification, equivalent substitution and improvement etc. made, should be included in the present invention's
Within protection domain.
Claims (10)
1. the method detecting multilane lane line, it is characterised in that described method includes:
The carriageway image of vehicle front is obtained by shooting part；
Described carriageway image is converted into gray level image；
Lane line region in described gray level image is carried out edge strengthening process and obtains edge strengthening image；
Obtain intensity slicing threshold value, according to described intensity slicing threshold value, described edge strengthening image is carried out two-value
Change processes and obtains binary image；
The outer edge point of fast lane line is judged in described binary image；
According to lane line feature detection and follow the tracks of described fast lane line；
Based on described fast lane line, in lane detection region, outside, detect and follow the tracks of kerb lane line,
Wherein, described kerb lane line detection region is inner side left-lane line with left region and inner side right lane line with the right side
Region.
Method the most according to claim 1, it is characterised in that described acquisition intensity slicing threshold value, root
According to described intensity slicing threshold value, described edge strengthening image is carried out binary conversion treatment and obtain binary image, bag
Include:
Obtain the intensity slicing threshold value of described left and right vehicle wheel both sides respectively, by described edge strengthening image division be
Left and right two parts；
Intensity slicing threshold value according to the described left and right sides, respectively two, the left and right to described edge strengthening image
Point carrying out binary conversion treatment obtains binary image.
Method the most according to claim 1, it is characterised in that described in lane detection region, outside
Middle detection also follows the tracks of kerb lane line, including:
Using the region from described fast lane alignment external expansion preset width as outer lane detection region,
Kerb lane line is detected and follows the tracks of in described outer lane detection region.
Method the most according to claim 1, it is characterised in that described method also includes:
If described kerb lane line is less than predetermined threshold value with the distance of described fast lane line, then judge described
Kerb lane line is invalid lane line.
Method the most according to claim 1, it is characterised in that described method also includes:
If in multiple carriageway images continuously, described kerb lane line and the base intersection point of described carriageway image
Within being in preset range, then judge that described kerb lane line is effective wagon diatom.
6. the device detecting multilane lane line, it is characterised in that described device includes:
Photographing module, for obtaining the carriageway image of vehicle front by shooting part；
Gray processing module, for being converted into gray level image by described carriageway image；
Edge strengthening module, obtains for lane line region in described gray level image carries out edge strengthening process
Edge strengthening image；
Binarization block, is used for obtaining intensity slicing threshold value, according to described intensity slicing threshold value to described edge
Strengthening image carries out binary conversion treatment and obtains binary image；
Edge detection module, for judging the outer edge point of fast lane line in described binary image；
First detection module, is used for according to lane line feature detection and follows the tracks of described fast lane line；
Second detection module, for based on described fast lane line, detects in lane detection region, outside
And follow the tracks of kerb lane line, wherein, described kerb lane line detection region is that inner side left-lane line is with left region
With inner side right lane line with right region.
Device the most according to claim 6, it is characterised in that described binarization block, is used for:
Obtain the intensity slicing threshold value of described left and right vehicle wheel both sides respectively, by described edge strengthening image division be
Left and right two parts；
Intensity slicing threshold value according to the described left and right sides, respectively two, the left and right to described edge strengthening image
Point carrying out binary conversion treatment obtains binary image.
Device the most according to claim 6, it is characterised in that described second detection module, is used for:
Using the region from described fast lane alignment external expansion preset width as outer lane detection region,
Kerb lane line is detected and follows the tracks of in described outer lane detection region.
Device the most according to claim 6, it is characterised in that described device also includes:
First judge module, if for described kerb lane line with the distance of described fast lane line less than pre-
If threshold value, then judge that described kerb lane line is invalid lane line.
Device the most according to claim 6, it is characterised in that described device also includes:
Second judge module, if be used in multiple carriageway images continuously, described kerb lane line and described track
Within the base intersection point of image is in preset range, then judge that described kerb lane line is effective wagon diatom.
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| CN113723382A (en) * | 2021-11-03 | 2021-11-30 | 深圳佑驾创新科技有限公司 | Method and device for lifting points of lane line and computer equipment |
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