CN102243705B - Method for positioning license plate based on edge detection - Google Patents
Method for positioning license plate based on edge detection Download PDFInfo
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- CN102243705B CN102243705B CN 201110120366 CN201110120366A CN102243705B CN 102243705 B CN102243705 B CN 102243705B CN 201110120366 CN201110120366 CN 201110120366 CN 201110120366 A CN201110120366 A CN 201110120366A CN 102243705 B CN102243705 B CN 102243705B
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Abstract
The invention provides a method for positioning a license plate by utilizing the edge information of a traffic image. The method comprises the following steps of: performing edge detection on a traffic image by using a Sobel operator, and binarizing the obtained gray-level edge image to obtain a binary edge image; then horizontally projecting the binary edge image in a vertical direction to obtain a vertical vector, binarizing the vertical vector, and scanning the vertical vector from top to bottom to obtain an initial row coordinate and an end row coordinate of a license plate region to realize the vertical positioning of the license plate; then obtaining the vertically positioned binary edge image by utilizing the initial row coordinate and the end row coordinate, vertically projecting the binary edge image in a horizontal direction to obtain a horizontal vector, binarizing the horizontal vector, and scanning the horizontal vector from left to right to obtain an initial line coordinate and an end line coordinate of the license plate region to realize the horizontal positioning of the license plate; and finally, positioning the license plate by using the initial row coordinate, the end row coordinate, the initial line coordinate and the end line coordinate. The method provided by the invention has higher precision for positioning the license plate and can also be used for positioning the license plate more accurately under the condition of low contrast (such as insufficient light at night).
Description
Technical field
The present invention relates to a kind of license plate locating method based on rim detection, its purpose is the license plate area in the traffic image is positioned, and belongs to the traffic monitoring technical field.
Background technology
Along with the development of economy and carrying out fast of urbanization process, China's motor vehicle is possessed quantity sharply to be increased, and the problem of traffic administration is more and more outstanding.Under many circumstances, often need vehicle is identified in order to carry out better traffic administration.Vehicle License Plate Recognition System is utilized the technology such as image processing, pattern-recognition automatically location and identification car plate, can improve widely the efficient of vehicle identification.It can be used for the fields such as parking lot management, traffic information collection, traffic police's inspection, customs's logistics monitoring, is with a wide range of applications.
Vehicle License Plate Recognition System comprises car plate location, Character segmentation, three modules of character recognition.In engineering is used, image acquisition is subjected to the impact of environmental factor larger, and under some specific environment (such as the insufficient light at night), the contrast of license plate image is very low, may cause inaccurate even location, car plate location less than car plate, thereby reduce the accuracy of car plate identification.In order to improve the performance of Vehicle License Plate Recognition System, must improve the accuracy of the lower car plate of low-contrast circumstances (such as the insufficient light at night) location.
By the retrieval of prior art document being found existing car plate location mainly contains the intensity-based saltus step and based on these two kinds of methods of texture analysis.In the situation that night insufficient light, gray scale and the texture difference of license plate area and non-license plate area are all less, these two kinds of methods all can not position car plate well.The invention provides a kind of license plate locating method that under low-contrast circumstances, still has high accuracy.Under low-contrast circumstances, the method is compared the intensity-based saltus step and is had higher accurate positioning based on the localization method of texture analysis.
Summary of the invention
Technical matters
The invention provides a kind of license plate locating method license plate locating method based on rim detection that in low contrast (such as the insufficient light at night) situation, still has high accuracy, the method have bearing accuracy high, low-contrast circumstances is had adaptive advantage.
Technical scheme
A kind of license plate locating method based on rim detection is characterized in that:
1. utilize the Sobel operator to carry out rim detection
If need to carry out the coloured image of car plate location is F
0, it being carried out gray processing obtain gray level image F, its line number, columns are respectively m and n, utilize horizontal Sobel operator S
1With vertical Sobel operator S
2Image F is carried out rim detection, obtain gradient image G
0,
G
0=|S
1*F|+|S
2*F|,
Then, utilize according to threshold value T
0To gradient image G
0Carry out binaryzation, obtain binary edge map G
1,
In the formula, threshold value T
0Be 15-20, G
0(x, y) is gradient image G
0Middle coordinate is the gray scale of the pixel of (x, y), G
1(x, y) is binary edge map G
1Middle coordinate is the value of the pixel of (x, y), if 1 this pixel of expression belongs to the edge, if 0 this pixel of expression does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
1Carry out horizontal projection, obtain vertical vector G
1x,
Utilize threshold value T
1To vertical vector G
1xCarry out binaryzation, obtain two-value vertical vector G '
1x,
In the formula, threshold value T
1Be generally 3-5, G '
1x(i
1) be 1 to be illustrated in binary edge map G
1I
1The row place exists characters on license plate, G '
1x(i
1) be 0 to be illustrated in binary edge map G
1I
1There is not characters on license plate in the row place,
Afterwards, to two-value vertical vector G '
1xScan from the top down, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
X1With end line coordinate P
X2Position, scanning step is as follows:
Step 1: establish two-value vertical vector G '
1xIn first numerical value be that the row-coordinate of 1 pixel is i
2, with row-coordinate i
2Give variable xbeg, and make variable xend=xbeg,
Step 2: i
2=i
2+ 1, if i
2=m+1 then forwards step 3 to, if i
2<m+1 then forwards step 4 to,
Step 3: if xend-xbeg>25 then show in gray level image F and detected car plate make P
X1=xbeg, P
X2=xend finishes scanning; If scanning is finished in xend-xbeg≤25 then show do not detect car plate in gray level image F,
Step 4: if i
2-xend≤6 and i
2-xbeg>25 then make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend≤6 and i
2-xbeg≤25 then make xend=i
2, return step 2; If i
2-xend>6 and xend-xbeg>25 item make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend>6 and xend-xbeg≤25 item make xbeg=i
2, xend=xbeg returns step 2,
Behind the end of scan, if detect car plate in the scanning process, then the initial row coordinate of license plate area P is positioned as P
X1, its end line coordinate is positioned as P
X2, obtain binary edge map G behind the perpendicular positioning according to positioning result
2,
G
2(i
2,j
2)=G
1(i
2+P
x1-1,j
2),
I wherein
2=1,2,3...... (P
X2-P
X1+ 1), j
2=1,2,3......n,
3. the location of car plate horizontal direction
To the binary edge map G behind the perpendicular positioning
2Carry out vertical projection, obtain horizontal vector G
2y,
Utilize threshold value T
2To horizontal vector G
2yCarry out binaryzation, obtain binarizing level vector G '
2y,
In the formula, threshold value T
2Be 15-20, G '
2y(i
3) be 1 to be illustrated in binary edge map G
2I
3There is characters on license plate in the row place, G '
2y(i
3) be 0 to be illustrated in binary edge map G
2I
3There is not characters on license plate in the row place,
Afterwards, to binarizing level vector G '
2yScan from left to right, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
Y1With end line coordinate P
Y2Position, scanning step is as follows:
Step 1: establish binarizing level vector G '
2yIn first numerical value be that the row coordinate of 1 pixel is i
4, with row coordinate i
4Give variable ybeg, and make variable yend=ybeg,
Step 2: i
4=i
4+ 1, if i
4=m+1 then forwards step 3 to, if i
4<m+1 then forwards step 4 to,
Step 3: if yend-ybeg>70 then show in gray level image F and detected car plate make P
Y1=ybeg, P
Y2=yend finishes scanning; If scanning is finished in yend-ybeg≤70 then show do not detect car plate in gray level image F,
Step 4: if i
4-yend≤15 and i
4-ybeg>70 then make P
Y1=ybeg, P
Y2=yend finishes scanning, if i
4-yend≤15 and i
4-ybeg≤70 then make yend=i
4, return step 2; If i
4-yend>15 and yend-ybeg>70 then make P
Y1=ybeg, P
Y2=yend finishes scanning, if
I4-yend>15 and yend-ybeg≤70 then make ybeg=i
4, yend=ybeg returns step 2,
Behind the end of scan, if detect car plate in the scanning process, then the initial row coordinate of license plate area P is positioned as P
Y1, its terminal point row coordinate is positioned as P
Y2, in conjunction with initial row coordinate P
X1With end line coordinate P
X2License plate area P after can obtaining locating is:
P(i
4,j
4)=F
0(i
4+P
x1-1,j
4+P
y1-1),
I wherein
4=1,2,3...... (P
X2-P
X1+ 1), j
4=1,2,3...... (P
Y2-P
Y1+ 1).
Beneficial effect
The car plate accurate positioning is high, and low contrast (such as the insufficient light at night) situation is had adaptability.License plate area has comprised regular numeral, letter and Chinese character.Under different shooting environmental, the marginal information of these character pictures compares its gray scale and texture information is more stable.The present invention utilizes marginal information that car plate is positioned, and has higher accurate positioning.Particularly under low-contrast circumstances, also can accurately locate car plate, compare the intensity-based saltus step and improved accurate positioning based on the localization method of texture analysis.
Description of drawings
Fig. 1 is the process flow diagram of car plate location.
Fig. 2 is the coloured image F that need to carry out the car plate location
0
Fig. 3 is gray level image F.
Fig. 4 is gradient image G
0
Fig. 5 is binary edge map G
1
Fig. 6 is the binary edge map G behind the perpendicular positioning
2
Fig. 7 is the license plate area P that the location obtains.
Fig. 8 is the binary edge map G behind the perpendicular positioning
2
Fig. 9 is to the binary edge map G behind the perpendicular positioning
2Carry out the perspective view that vertical projection obtains.
Figure 10 is the license plate area P that final location obtains.
Embodiment
Instantiation of the present invention is described as follows in conjunction with Fig. 2-7:
1. utilize the Sobel operator to carry out rim detection
If need to carry out the coloured image of car plate location is F
0, as shown in Figure 2, it is carried out gray processing obtain gray level image F, as shown in Figure 3, its line number, columns are respectively 768 and 576, utilize horizontal Sobel operator S
1With vertical Sobel operator S
2Image F is carried out rim detection, obtain gradient image G
0, as shown in Figure 4,
G
0=|S
1*F|+|S
2*F|,
In the formula,
* represent convolution algorithm,
Then, utilize according to threshold value T
0To gradient image G
0Carry out binaryzation, obtain binary edge map G
1, as shown in Figure 5,
In the formula, threshold value T
0Be 15, G
0(x, y) is gradient image G
0Middle coordinate is the gray scale of the pixel of (x, y), G
1(x, y) is binary edge map G
1Middle coordinate is the value of the pixel of (x, y), if 1 this pixel of expression belongs to the edge, if 0 this pixel of expression does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
1Carry out horizontal projection, as shown in Figure 6, obtain vertical vector G
1x,
Utilize threshold value T
1To vertical vector G
1xCarry out binaryzation, obtain two-value vertical vector G '
1x,
In the formula, threshold value T
1Be 5, G '
1x(i
1) be 1 to be illustrated in binary edge map G
1I
1The row place exists characters on license plate, G '
1x(i
1) be 0 to be illustrated in binary edge map G
1I
1There is not characters on license plate in the row place,
Afterwards, to two-value vertical vector G '
1xScan from the top down, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
X1With end line coordinate P
X2Position, as shown in Figure 7, scanning step is as follows:
Step 1: establish two-value vertical vector G '
1xIn first numerical value be that the row-coordinate of 1 pixel is i
2, with row-coordinate i
2Give variable xbeg, and make variable xend=xbeg,
Step 2: i
2=i
2+ 1, if i
2=m+1 then forwards step 3 to, if i
2<m+1 then forwards step 4 to,
Step 3: if xend-xbeg>25 then show in gray level image F and detected car plate make P
X1=xbeg, P
X2=xend finishes scanning; If scanning is finished in xend-xbeg≤25 then show do not detect car plate in gray level image F,
Step 4: if i
2-xend≤6 and i
2-xbeg>25 then make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend≤6 and i
2-xbeg≤25 then make xend=i
2, return step 2; If i
2-xend>6 and xend-xbeg>25 item make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend>6 and xend-xbeg≤25 item make xbeg=i
2, xend=xbeg returns step 2,
In scanning process, detect car plate, then the initial row coordinate P of license plate area P
X1Be positioned as 387, its end line coordinate P
X2Be positioned as 409, obtain binary edge map G behind the perpendicular positioning according to positioning result
2, as shown in Figure 8,
G
2(i
2,j
2)=G
1(i
2+386,j
2),
I wherein
2=1,2,3......23, j
2=1,2,3......n,
3. the location of car plate horizontal direction
To the binary edge map G behind the perpendicular positioning
2Carry out vertical projection, as shown in Figure 9, obtain horizontal vector G
2y,
Utilize threshold value T
2To horizontal vector G
2yCarry out binaryzation, obtain binarizing level vector G '
2y,
In the formula, threshold value T
2Be 15, G '
2y(i
3) be 1 to be illustrated in binary edge map G
2I
3There is characters on license plate in the row place, G '
2y(i
3) be 0 to be illustrated in binary edge map G
2I
3There is not characters on license plate in the row place,
Afterwards, to binarizing level vector G '
2yScan from left to right, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
Y1With end line coordinate P
Y2Position, as shown in Figure 7, scanning step is as follows:
Step 1: establish binarizing level vector G '
2yIn first numerical value be that the row coordinate of 1 pixel is i
4, with row coordinate i
4Give variable ybeg, and make variable yend=ybeg,
Step 2: i
4=i
4+ 1, if i
4=m+1 then forwards step 3 to, if i
4<m+1 then forwards step 4 to,
Step 3: if yend-ybeg>70 then show in gray level image F and detected car plate make P
Y1=ybeg, P
Y2=yend finishes scanning; If scanning is finished in yend-ybeg≤70 then show do not detect car plate in gray level image F,
Step 4: if i
4-yend≤15 and i
4-ybeg>70 then make P
Y1=ybeg, P
Y2=yend finishes scanning, if i
4-yend≤15 and i
4-ybeg≤70 then make yend=i
4, return step 2; If i
4-yend>15 and yend-ybeg>70 then make P
Y1=ybeg, P
Y2=yend finishes scanning, if i
4-yend>15 and yend-ybeg≤70 then make ybeg=i
4, yend=ybeg returns step 2,
In scanning process, detect car plate, then the initial row coordinate P of license plate area P
Y1Be positioned as 85, its terminal point row coordinate P
Y2Be positioned as 210, in conjunction with initial row coordinate P
X1With end line coordinate P
X2License plate area P after can obtaining locating is:
P(i
4,j
4)=F
0(i
4+386,j
4+84),
I wherein
4=1,2,3......23, j
4=1,2,3......117,
The license plate area P that final location obtains as shown in figure 10.
Claims (1)
1. license plate locating method based on rim detection is characterized in that:
1. utilize the Sobel operator to carry out rim detection
If need to carry out the coloured image of car plate location is F
0, it being carried out gray processing obtain gray level image F, its line number, columns are respectively m and n, utilize horizontal Sobel operator S
1With vertical Sobel operator S
2Image F is carried out rim detection, obtain gradient image G
0,
G
0=|S
1*F|+|S
2*F|,
In the formula,
* represent convolution algorithm,
Then, utilize threshold value T
0To gradient image G
0Carry out binaryzation, obtain binary edge map G
1,
In the formula, threshold value T
0Be 15-20, G
0(x, y) is gradient image G
0Middle coordinate is the gray scale of the pixel of (x, y), G
1(x, y) is binary edge map G
1Middle coordinate is the value of the pixel of (x, y), if 1 this pixel of expression belongs to the edge, if 0 this pixel of expression does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
1Carry out horizontal projection, obtain vertical vector G
1x,
Utilize threshold value G
1To vertical vector G
1xCarry out binaryzation, obtain the two-value vertical vector
In the formula, threshold value T
1Be 3-5,
Be 1 to be illustrated in binary edge map G
1I
1There is characters on license plate in the row place,
Be 0 to be illustrated in binary edge map G
1I
1There is not characters on license plate in the row place,
Afterwards, to the two-value vertical vector
Scan from the top down, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
X1With end line coordinate P
X2Position, behind the end of scan, obtain binary edge map G behind the perpendicular positioning according to positioning result
2,
G
2(i
2,j
2)=G
1(i
2+P
x1-1,j
2),
I wherein
2=1,2,3...... (P
X2-P
X1+ 1), j
2=1,2,3......n,
Concrete scanning step is as follows:
Step 1: establish the two-value vertical vector
In first numerical value be that the row-coordinate of 1 pixel is i
2, with row-coordinate i
2Give variable xbeg, and make variable xend=xbeg,
Step 2: i
2=i
2+ 1, if i
2=m+1 then forwards step 3 to, if i
2<m+1 then forwards step 4 to,
Step 3: if xend-xbeg〉25 then show in gray level image F and detected car plate, make P
X1=xbeg, P
X2=xend finishes scanning; If scanning is finished in xend-xbeg≤25 then show do not detect car plate in gray level image F,
Step 4: if i
2-xend≤6 and i
2-xbeg〉25, then make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend≤6 and i
2-xbeg≤25 then make xend=i
2, return step 2; If i
2-xend〉6 and xend-xbeg 25 items make P
X1=xbeg, P
X2=xend finishes scanning, if i
2-xend〉6 and xend-xbeg≤25 item make xbeg=i
2, xend=xbeg returns step 2,
3. the location of car plate horizontal direction
To the binary edge map G behind the perpendicular positioning
2Carry out vertical projection, obtain horizontal vector G
2y,
Utilize threshold value T
2To horizontal vector T
2yCarry out binaryzation, obtain the binarizing level vector
In the formula, threshold value T
2Be 15-20,
Be 1 to be illustrated in binary edge map G
2I
3There is characters on license plate in the row place,
Be 0 to be illustrated in binary edge map G
2I
3There is not characters on license plate in the row place,
Afterwards, to the binarizing level vector
Scan from left to right, if detect license plate area P by scanning, then to the initial row coordinate P of license plate area P
Y1With terminal point row coordinate P
Y2Position, behind the end of scan, in conjunction with initial row coordinate P
X1With end line coordinate P
X2License plate area P after can obtaining locating is:
P(i
4,j
4)=F
0(i
4+P
x1-1,j
4+P
y1-1),
I wherein
4=1,2,3...... (P
X2-P
X1+ 1), j
4=1,2,3...... (P
Y2-P
Y1+ 1),
Concrete scanning step is as follows:
Step 1: establish the binarizing level vector
In first numerical value be that the row coordinate of 1 pixel is i
4, with row coordinate i
4Give variable ybeg, and make variable yend=ybeg,
Step 2: i
4=i
4+ 1, if i
4=n+1 then forwards step 3 to, if i
4<n+1 then forwards step 4 to,
Step 3: if yend-ybeg〉70 then show in gray level image F and detected car plate, make P
Y1=ybeg, P
Y2=yend finishes scanning; If scanning is finished in yend-ybeg≤70 then show do not detect car plate in gray level image F,
Step 4: if i
4-yend≤15 and i
4-ybeg〉70, then make P
Y1=ybeg, P
Y2=yend finishes scanning, if i
4-yend≤15 and i
4-ybeg≤70 then make yend=i
4, return step 2; If i
4-yend〉15 and yend-ybeg 70, then make P
Y1=ybeg, P
Y2=yend finishes scanning, if i
4-yend>15 and yend-ybeg≤70 then make ybeg=i
4, yend=ybeg returns step 2.
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TWI592905B (en) * | 2016-03-30 | 2017-07-21 | 聯詠科技股份有限公司 | Method and apparatus for performing registration plate detection |
CN107798323B (en) * | 2016-08-29 | 2020-12-29 | 北京君正集成电路股份有限公司 | License plate image positioning method and device |
CN106504294B (en) * | 2016-10-17 | 2019-04-26 | 浙江工业大学 | RGBD image vector method based on diffusion profile |
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CN110689016B (en) * | 2018-07-05 | 2023-04-18 | 山东华软金盾软件股份有限公司 | License plate image coarse positioning method |
CN109522834A (en) * | 2018-11-10 | 2019-03-26 | 国网电力科学研究院武汉南瑞有限责任公司 | A kind of nameplate recognition methods of power equipment |
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