CN102243705A  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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 CN102243705A CN102243705A CN 201110120366 CN201110120366A CN102243705A CN 102243705 A CN102243705 A CN 102243705A CN 201110120366 CN201110120366 CN 201110120366 CN 201110120366 A CN201110120366 A CN 201110120366A CN 102243705 A CN102243705 A CN 102243705A
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 license plate
 coordinate
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 238000003708 edge detection Methods 0.000 title abstract 2
 238000000034 method Methods 0.000 claims description 9
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 238000005516 engineering processes Methods 0.000 description 2
 230000004807 localization Effects 0.000 description 2
 230000003044 adaptive Effects 0.000 description 1
 230000018109 developmental process Effects 0.000 description 1
 238000010586 diagrams Methods 0.000 description 1
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 238000003909 pattern recognition Methods 0.000 description 1
 230000011218 segmentation Effects 0.000 description 1
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 graylevel 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 carrying out fast of constant development of economy and 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 discerned in order to carry out traffic administration better.Vehicle License Plate Recognition System is utilized technology such as Flame Image Process, patternrecognition location and identification car plate automatically, can improve the efficient of vehicle identification widely.It can be used for 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 Effect of Environmental bigger, 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 lowcontrast circumstances (such as the insufficient light at the night) accuracy of car plate location down.
By the retrieval of prior art document being found existing car plate location mainly contains based on Gray Level Jump with based on these two kinds of methods of texture analysis.Under the situation of insufficient light at night, the gray scale of license plate area and nonlicense plate area and texture difference are all less, and these two kinds of methods all can not position car plate well.The invention provides a kind of license plate locating method that under lowcontrast circumstances, still has high accuracy.Under lowcontrast circumstances, this method is compared based on Gray Level Jump with based on the localization method of texture analysis has higher accurate positioning.
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 still has high accuracy under low contrast (such as the insufficient light at night) situation, this method has the bearing accuracy height, lowcontrast 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 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
_{1}With vertical Sobel operator S
_{2}Image 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 according to threshold value T
_{0}To gradient image G
_{0}Carry out binaryzation, obtain binary edge map G
_{1},
In the formula, threshold value T
_{0}Be 1520, G
_{0}(x y) is gradient image G
_{0}Middle coordinate is (x, the gray scale of pixel y), G
_{1}(x y) is binary edge map G
_{1}In coordinate be (x, the value of pixel y) is if 1 this pixel of expression belongs to the edge, if 0 represents that this pixel does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
_{1}Carry out horizontal projection, obtain vertical vector G
_{1x},
Utilize threshold value T
_{1}To vertical vector G
_{1x}Carry out binaryzation, obtain twovalue vertical vector G '
_{1x},
In the formula, threshold value T
_{1}Be generally 35, G '
_{1x}(i
_{1}) be 1 to be illustrated in binary edge map G
_{1}I
_{1}The row place exists characters on license plate, G '
_{1x}(i
_{1}) be 0 to be illustrated in binary edge map G
_{1}I
_{1}There is not characters on license plate in the row place,
Afterwards, to twovalue vertical vector G '
_{1x}Scan from the top down, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{X1}With end line coordinate P
_{X2}Position, scanning step is as follows:
Step 1: establish twovalue vertical vector G '
_{1x}In first numerical value be that the rowcoordinate of 1 pixel is i
_{2}, with rowcoordinate i
_{2}Give 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 xendxbeg＞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 xendxbeg≤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 xendxbeg＞25 item make P
_{X1}=xbeg, P
_{X2}=xend finishes scanning, if i
_{2}xend＞6 and xendxbeg≤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
_{2}Carry out vertical projection, obtain horizontal vector G
_{2y},
Utilize threshold value T
_{2}To horizontal vector G
_{2y}Carry out binaryzation, obtain binarizing level vector G '
_{2y},
In the formula, threshold value T
_{2}Be 1520, G '
_{2y}(i
_{3}) be 1 to be illustrated in binary edge map G
_{2}I
_{3}There is characters on license plate in the row place, G '
_{2y}(i
_{3}) be 0 to be illustrated in binary edge map G
_{2}I
_{3}There is not characters on license plate in the row place,
Afterwards, to binarizing level vector G '
_{2y}Scan from left to right, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{Y1}With end line coordinate P
_{Y2}Position, scanning step is as follows:
Step 1: establish binarizing level vector G '
_{2y}In first numerical value be that the row coordinate of 1 pixel is i
_{4}, with row coordinate i
_{4}Give 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 yendybeg＞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 yendybeg≤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 yendybeg＞70 then make P
_{Y1}=ybeg, P
_{Y2}=yend finishes scanning, if
_{I4}yend＞15 and yendybeg≤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
_{X1}With end line coordinate P
_{X2}License 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
Car plate accurate positioning height has adaptability to low contrast (such as the insufficient light at night) situation.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 lowcontrast circumstances, also can accurately locate, compare based on Gray Level Jump with based on the localization method of texture analysis and improved accurate positioning car plate.
Description of drawings
Fig. 1 is the process flow diagram of car plate location.
Fig. 2 is the coloured image F that need 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
_{2}Carry 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. 27:
1. utilize the Sobel operator to carry out rim detection
If need 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
_{1}With vertical Sobel operator S
_{2}Image 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
_{0}To gradient image G
_{0}Carry out binaryzation, obtain binary edge map G
_{1}, as shown in Figure 5,
In the formula, threshold value T
_{0}Be 15, G
_{0}(x y) is gradient image G
_{0}Middle coordinate is (x, the gray scale of pixel y), G
_{1}(x y) is binary edge map G
_{1}In coordinate be (x, the value of pixel y) is if 1 this pixel of expression belongs to the edge, if 0 represents that this pixel does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
_{1}Carry out horizontal projection, as shown in Figure 6, obtain vertical vector G
_{1x},
Utilize threshold value T
_{1}To vertical vector G
_{1x}Carry out binaryzation, obtain twovalue vertical vector G '
_{1x},
In the formula, threshold value T
_{1}Be 5, G '
_{1x}(i
_{1}) be 1 to be illustrated in binary edge map G
_{1}I
_{1}The row place exists characters on license plate, G '
_{1x}(i
_{1}) be 0 to be illustrated in binary edge map G
_{1}I
_{1}There is not characters on license plate in the row place,
Afterwards, to twovalue vertical vector G '
_{1x}Scan from the top down, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{X1}With end line coordinate P
_{X2}Position, as shown in Figure 7, scanning step is as follows:
Step 1: establish twovalue vertical vector G '
_{1x}In first numerical value be that the rowcoordinate of 1 pixel is i
_{2}, with rowcoordinate i
_{2}Give 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 xendxbeg＞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 xendxbeg≤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 xendxbeg＞25 item make P
_{X1}=xbeg, P
_{X2}=xend finishes scanning, if i
_{2}xend＞6 and xendxbeg≤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
_{X1}Be positioned as 387, its end line coordinate P
_{X2}Be 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
_{2}Carry out vertical projection, as shown in Figure 9, obtain horizontal vector G
_{2y},
Utilize threshold value T
_{2}To horizontal vector G
_{2y}Carry out binaryzation, obtain binarizing level vector G '
_{2y},
In the formula, threshold value T
_{2}Be 15, G '
_{2y}(i
_{3}) be 1 to be illustrated in binary edge map G
_{2}I
_{3}There is characters on license plate in the row place, G '
_{2y}(i
_{3}) be 0 to be illustrated in binary edge map G
_{2}I
_{3}There is not characters on license plate in the row place,
Afterwards, to binarizing level vector G '
_{2y}Scan from left to right, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{Y1}With end line coordinate P
_{Y2}Position, as shown in Figure 7, scanning step is as follows:
Step 1: establish binarizing level vector G '
_{2y}In first numerical value be that the row coordinate of 1 pixel is i
_{4}, with row coordinate i
_{4}Give 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 yendybeg＞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 yendybeg≤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 yendybeg＞70 then make P
_{Y1}=ybeg, P
_{Y2}=yend finishes scanning, if i
_{4}yend＞15 and yendybeg≤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
_{Y1}Be positioned as 85, its terminal point row coordinate P
_{Y2}Be positioned as 210, in conjunction with initial row coordinate P
_{X1}With end line coordinate P
_{X2}License 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 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
_{1}With vertical Sobel operator S
_{2}Image 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 according to threshold value T
_{0}To gradient image G
_{0}Carry out binaryzation, obtain binary edge map G
_{1},
In the formula, threshold value T
_{0}Be 1520, G
_{0}(x y) is gradient image G
_{0}Middle coordinate is (x, the gray scale of pixel y), G
_{1}(x y) is binary edge map G
_{1}In coordinate be (x, the value of pixel y) is if 1 this pixel of expression belongs to the edge, if 0 represents that this pixel does not belong to the edge;
2. the location of car plate vertical direction
To binary edge map G
_{1}Carry out horizontal projection, obtain vertical vector C
_{1x},
Utilize threshold value T1 to vertical vector G
_{1x}Carry out binaryzation, obtain twovalue vertical vector G '
_{1x},
In the formula, threshold value T
_{1}Be generally 35, G '
_{1x}(i
_{1}) be 1 to be illustrated in binary edge map G
_{1}I
_{1}The row place exists characters on license plate, G '
_{1x}(i
_{1}) be 0 to be illustrated in binary edge map G
_{1}I
_{1}There is not characters on license plate in the row place,
Afterwards, to twovalue vertical vector G '
_{1x}Scan from the top down, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{X1}With end line coordinate P
_{X2}Position, scanning step is as follows:
Step 1: establish twovalue vertical vector G '
_{1x}In first numerical value be that the rowcoordinate of 1 pixel is i
_{2}, with rowcoordinate i
_{2}Give 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 xendxbeg＞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 xendxbeg≤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 xendxbeg＞25 item make P
_{X1}=xbeg, P
_{X2}=xend finishes scanning, if i
_{2}xend＞6 and xendxbeg≤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
_{2}Carry out vertical projection, obtain horizontal vector G
_{2y},
Utilize threshold value T
_{2}To horizontal vector G
_{2y}Carry out binaryzation, obtain binarizing level vector G '
_{2y},
In the formula, threshold value T
_{2}Be 1520, G '
_{2y}(i
_{3}) be 1 to be illustrated in binary edge map G
_{2}I
_{3}There is characters on license plate in the row place, G '
_{2y}(i
_{3}) be 0 to be illustrated in binary edge map G
_{2}I
_{3}There is not characters on license plate in the row place,
Afterwards, to binarizing level vector G '
_{2y}Scan from left to right, if detect license plate area P, then to the initial row coordinate P of license plate area P by scanning
_{Y1}With end line coordinate P
_{Y2}Position, scanning step is as follows:
Step 1: establish binarizing level vector G '
_{2y}In first numerical value be that the row coordinate of 1 pixel is i
_{4}, with row coordinate i
_{4}Give 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 yendybeg＞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 yendybeg≤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 yendybeg＞70 then make P
_{Y1}=ybeg, P
_{Y2}=yend finishes scanning, if i
_{4}yend＞15 and yendybeg≤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
_{X1}With end line coordinate P
_{X2}License 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).
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Citations (4)
Publication number  Priority date  Publication date  Assignee  Title 

JPS63131281A (en) *  19861120  19880603  Matsushita Electric Ind Co Ltd  Automatic number plate recognizer 
US7302098B2 (en) *  20041203  20071127  Motorola, Inc.  Character segmentation method and apparatus 
CN101183425A (en) *  20071220  20080521  四川川大智胜软件股份有限公司  Guangdong and Hong Kong license plate locating method 
CN101303803A (en) *  20080611  20081112  北京中星微电子有限公司  Method and system for discriminating license plate 

2011
 20110509 CN CN 201110120366 patent/CN102243705B/en not_active IP Right Cessation
Patent Citations (4)
Publication number  Priority date  Publication date  Assignee  Title 

JPS63131281A (en) *  19861120  19880603  Matsushita Electric Ind Co Ltd  Automatic number plate recognizer 
US7302098B2 (en) *  20041203  20071127  Motorola, Inc.  Character segmentation method and apparatus 
CN101183425A (en) *  20071220  20080521  四川川大智胜软件股份有限公司  Guangdong and Hong Kong license plate locating method 
CN101303803A (en) *  20080611  20081112  北京中星微电子有限公司  Method and system for discriminating license plate 
NonPatent Citations (3)
Title 

《科技信息》 20090120 蔡立平 车牌识别系统中的车牌定位算法研究 9192 , 第2期 * 
《科技通报》 20100531 卓均飞等 基于边缘检测和投影法的车牌定位算法研究 438441 第26卷, 第3期 * 
《第十三届全国图象图形学学术会议论文集》 20061231 黄文楷等 基于灰度图像的车牌定位算法的研究 419422 , * 
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CN107292303B (en) *  20160330  20200421  联咏科技股份有限公司  Method and apparatus for license plate inspection with edge type sliding concentric window 
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