CN106485182A - A kind of fuzzy Q R code restored method based on affine transformation - Google Patents
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Abstract
The invention discloses providing a kind of method calibrating traditional image recovery method with QR code feature to be combined, traditional images restored method is make use of to obtain the preferable image of quality, the feature that again make use of QR code obtains the QR code of a standard, more quickness and high efficiency provide accurate QR code to position image for automatic guide vehicle, and obtain the fuzzy Q R code motion blur image restoration method based on affine transformation of the attitude information in automatic guide vehicle running.The present invention utilizes multi-resolution hierarchy, obtains ROI image, and image restoration time can be greatly lowered.Through calibration QR code, very high with the QR code similarity of standard it is ensured that identification.
Description
Technical field
The invention belongs to image processing field is and in particular to a kind of AGV locating module motion blur based on QR code restores
Method.
Background technology
With the development of industrial automation technology, automatic guide vehicle (AGV) is widely adopted, and automatic guided vehicle can be by
Route automatic running according to instruction, it is not necessary to artificial interfere, therefore, it is possible to effectively improve industrial automation, improves conevying efficiency.
Existing automatic guide vehicle air navigation aid is mainly the method such as magnetic stripe guiding, laser aiming, but these methods are all
There is the limitation of itself, in recent years, with scientific and technological development, also occur in that some new location and navigation technologies, based on Quick Response Code
The automatic guide vehicle air navigation aid of positioning, this visual guidance method can effectively improve the soft of the path design of automatic guide vehicle
Property, but because two-dimension code structure is more complicated, image that automatic guided vehicle collects in motor process be fuzzy it is impossible to
Direct Recognition, needs motion blur image restoration, conventional motion blur image restoration algorithm.
Image restoration is a hot spot technology in recent years, its purpose be restore from the observed image degrading real
Image, its mathematical model can be described as formula (1)：
G (x, y)=f (x, y) * h (x, y)+n (x, y) (1)；
Wherein, x, y are image space coordinates, and the image upper left corner is initial point, and g (x, y) is the observed image degrading, f (x, y)
It is true picture, h (x, y) is degradation model, n (x, y) is additive noise.By Fourier transformation, this model can be in frequency domain table
It is shown as formula (2)：
G (u, v)=F (u, v) H (u, v)+N (u, v) (2)；
Wherein, u, v represent discrete frequency coordinate, G (u, v), F (u, v), H (u, v), N (u, v) be respectively g (x, y), f (x,
Y), h (x, y), the Fourier transformation of n (x, y), H (u, v) be also called point spread function (point spread function,
PSF), wherein in PSF, most important two parameters are blur direction and fuzzy distance respectively.Image restoration is exactly to find one again
Former wave filter, obtains the estimation of f (x, y)
Restore to solve motion blur, also occur in that some image recovery methods in recent years, but automatic guided vehicle exists
It is linear uniform motion in work process, that is, the direction of motion is all known with speed, such as China Patent No.
Double iterative mixing blind restoration methods that CN201510445795.1 is announced, its iterative algorithm process time is long, recovery effect
Bad, do not make full use of two parameters of known PSF it is impossible to ensure the absolutely identification of Quick Response Code, be not suitable for using
Make the image recovery method of automatic guided vehicle, if the speed of automatic guided vehicle is slightly fast, Quick Response Code None- identified will be made, lead
Cause can not effectively position, and the scheduling of impact automatic guided vehicle is realized, or even can produce derailing, causes inevitably to lose.
Content of the invention
For above-mentioned prior art exist defect, it is an object of the invention to provide a kind of by traditional image restoration side
The method that method is calibrated with QR code feature is combined, that is, make use of traditional images restored method to obtain the preferable image of quality, and
The feature that make use of QR code obtains the QR code of a standard, more quickness and high efficiency provide accurate QR code fixed for automatic guide vehicle
Bit image, and obtain the fuzzy Q R code motion mould based on affine transformation of the attitude information in automatic guide vehicle running
Paste image recovery method.
For achieving the above object, the technical scheme is that：A kind of fuzzy Q R code based on affine transformation restores
Method, comprises the following steps：
Step (1), using the constant principle of moment of Hu, comprises the region of QR code in the motion blur image calculating parked
ROI image；Step includes：
Step (1.1), using Gaussian image pyramid, downward to motion blur image three times down-sampled；
Step (1.2), detects the marginal information of down-sampled image downwards, calculates the Hu not bending moment of all marginal informations, root
According to Hu, bending moment does not obtain the edge that size meets, as the edge of QR code；
Step (1.3), comprises the edge obtaining in step (1.2), obtains four angle points of minimum rectangle with minimum rectangle,
It is multiplied by 3 respectively, the minimum obtaining QR code in motion blur image comprises rectangle, and segmentation figure picture obtains ROI image；
Step (2), carries out preliminary motion and obscures again with the ROI image that traditional image recovery method obtains to step (1)
Former；Step includes：
Step (2.1), according to the direction of motion of automatic guided vehicle, obtains the motion blur direction of ROI image；
Step (2.2), according to the movement velocity of automatic guided vehicle, obtains the motion blur distance of ROI image；
Step (2.3), using vanishing moment number be 4 db4 wavelet transformation, obtain 4 sub- band diagrams of ROI image
Picture, is that low frequency part LL of original image, vertical low frequency part HL of horizontal high-frequent of original image, the horizontal low frequencies of original image hang down respectively
Straight HFS LH, the diagonal HFS HH of original image；Motion blur side is obtained in (2.2) according to step (2.1), step
To with motion blur distance, using Wiener filtering to LL motion blur restore, using Laplace operator to LH, HL, HH edge
Keep；
Step (2.4), using wavelet inverse transformation, 4 sub- band images is reconstructed the ROI image of recovery；
Step (3), using run-length encoding, obtains four angle points of QR code in the ROI image restoring, step includes：
Step (3.1), according to grey level histogram, using Otsu threshold method, the ROI image binaryzation that will restore；
Step (3.2), using median filter, dispels the salt-pepper noise in binaryzation ROI image and ringing effect；
Step (3.3), calculates the run-length encoding of binaryzation ROI image, according to the feature of QR code, is calculated binaryzation
Four angle points of QR code in ROI image；
Step (4), using Homography matrix and Principle of Affine Transformation, is calculated the binaryzation just put and restores QR code
Image, step includes：
Step (4.1), according to size in broad image for the QR code, obtains QR code-phase truer QR code in broad image
Amplification, is calculated four angle points of amplification；
Step (4.2), using four obtained in four angle points of the QR code obtaining in step (3.3) and step (4.1)
Angle point, is calculated the linear solution of Homography matrix；
Step (4.3), using Principle of Affine Transformation, is calculated the recovery QR code just put；
Step (5), the recovery just put QR code division is segmented into N*N module, according to the feature of QR code, travels through N*N mould
Block, according to the feature of each module, current block is entered as black or white.
The invention has the beneficial effects as follows：
The present invention having the beneficial effects that compared with prior art：
1st, the present invention utilizes multi-resolution hierarchy, obtains ROI image, and image restoration time can be greatly lowered.
2nd, the present invention utilizes wavelet transformation, can improve the robustness of image restoration, improves image restoration effect.
3rd, through calibration QR code, very high with the QR code similarity of standard it is ensured that identification.
4th, algorithm is simple, it is easy to accomplish, real-time.
5 present invention is particularly suitable for motion blur do the automatic guided vehicle work process of locating module using QR code in
Image restoration.
Term is explained：
QR code is one kind of two-dimensional bar code, and QR is derived from the abbreviation of English " Quick Response ", i.e. rapid-action meaning
Think, wish that QR code can allow its content quickly be decoded from inventor.QR code can store additional information than common bar code, also need not
Need adjusting to a line scanning device in scanning as common bar code.QR code can quickly read, compared with bar code before, QR code
More rich information can be stored, including to word, URL address and other kinds of data encryption.
ROI, is region of interest abbreviation, refers to that sample determines for selecting in the data set of special-purpose
Subset.The concept of one ROI is conventional in many applications, is exactly certain use of given image in image processing field
Data in the region of special-purpose.
Brief description
When considered in conjunction with the accompanying drawings, by referring to detailed description below, can more completely more fully understand the present invention with
And easily learn the adjoint advantage of many of which, but accompanying drawing described herein is used for providing a further understanding of the present invention,
Constitute the part of the present invention, the schematic description and description of the present invention is used for explaining the present invention, does not constitute to this
Bright improper restriction, wherein：
Fig. 1 is three gaussian pyramid down-sampled images downwards in embodiment step (1)；
Fig. 2 is according to the Hu satisfactory profile that bending moment does not obtain in embodiment step (1)；
Fig. 3 is the ROI image that in embodiment step (1), segmentation obtains；
Fig. 4 is that in embodiment step (2), motion blur restores ROI image；
Fig. 5 is affine transformation schematic diagram in embodiment step (4)；
Fig. 6 is the recovery QR code just put in embodiment step (4)；
Fig. 7 is the module map that in embodiment step (5), the Image Segmentation Methods Based on Features according to QR code becomes；
Fig. 8 is the restoration result in embodiment step (5) to broad image.
Specific embodiment
Below in conjunction with accompanying drawing to the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described.
The present invention comprises five steps, and concrete methods of realizing is as follows：
Step (1), utilize Hu constant principle of moment, in the motion blur image calculating parked, comprise the region of QR code
ROI (region of interest) image.Concrete methods of realizing is as follows：
Step (1.1) utilizes Gaussian image pyramid, three samplings downward to motion blur image, down-sampled knot downwards
Fruit as shown in figure 1, gaussian pyramid down-sampled formula (1) is downwards：
Wherein x, y are image space coordinates, and the image upper left corner is initial point (0,0), Gn+1(x, y) is (n+1)th grade of down-sampled figure
Picture, Gn(x, y) is n-th grade of down-sampled image, and W (a, b)=W (a) * W (b) is the Gaussian convolution core that length is 5, and W (a) is x=a
The value of Gaussian convolution core at point, W (b) points out the value of Gaussian convolution core for x=b.
Step (1.2) uses Canny operator to detect the marginal information of down-sampled image downwards, calculates the Hu at all edges not
Bending moment, the formula (4) of Hu not bending moment is as follows：
Wherein p=0,1,2......, q=0,1,2......, m00Area for geometric moment.
Calculate the area at all edges that Canny operator edge detection obtains, obtain wherein satisfactory edge, regard
It is the edge of QR code, the edge of QR code is as shown in Figure 2.
Step (1.3) minimum rectangle comprises the edge obtaining in step (1.2), obtains four angle points of minimum rectangle,
It is multiplied by 3 respectively, the minimum obtaining QR code in motion blur image comprises rectangle, and it is as shown in Figure 3 that segmentation figure picture obtains ROI image.
Step (2), carries out preliminary motion smear restoration with traditional image recovery method to ROI image.Implemented
Journey is as follows：
Step (2.1), automatic guided vehicle moves along y direction all the time, so the motion blur direction of ROI image is 90 °.
Step (2.2), the movement velocity of automatic guided vehicle is v, and the time of exposure of industrial camera is t, so ROI image
Fuzzy distance be vt.
Step (2.3), using vanishing moment number be 4 " db4 " small echo, scale coefficient is：
{0.325803,1.010946,0.892200,-0.039575,-0.264507,0.043616,0.023252,-
0.014987}
Wavelet transformation is given by formula (5) and (6)：
WhereinIt is the of original image respectively
j0The value of x=m with y=n low frequency part (LL), the value of the vertical low frequency part of horizontal high-frequent (HL), level in four frequency sub-band of level
The value of low frequency vertical HFS (LH), the value of diagonal HFS (HH), H, V, D are respectively intended to identify three high frequency frequencies
Section.M and N is width and the height of image resolution ratio,
For jth0Level scaling function andValue at x=m, y=n for the j-th stage wavelet function, its
Calculating process is as follows：
X, y are represented with t, whereinFor scaling function,
For wavelet function.
H (n) is scale coefficient, and the number of vanishing moment is that 4 " db4 " wavelet scale coefficient is：
{0.325803,1.010946,0.892200,-0.039575,-0.264507,0.043616,0.023252,-
0.014987}
LL frequency sub-band is restored using Wiener filtering, Wiener filtering is given by：
WhereinIt isFourier transformation, H*(u, v) is the conjugate matrices of h (x, y) Fourier transformation, and K is
Special constant, generally takes less than 1.
HL, LH, HH frequency sub-band is kept using Laplace operator edge respectively, Laplace operator is as follows：
According to process after LL, HL, LH, HH frequency sub-band, reconstruction image, as shown in Figure 4.
Step (3), using run-length encoding, obtains four angle points of QR code in the ROI image restoring.Implement process
For：
Step (3.1), according to grey level histogram, using Otsu threshold method, the ROI image binaryzation that will restore.
Step (3.2), using median filter, dispels the salt-pepper noise in binaryzation ROI image and ringing effect.
Step (3.3), calculates the run-length encoding of binaryzation ROI image, according to the feature of QR code, is calculated binaryzation
A in four angle points of QR code in ROI image, such as Fig. 51、A2、A3、A4, wherein XS-axis、YS- axis is binaryzation ROI image
Coordinate system, zero is O (xs,ys).
Step (4), using Homography matrix and Principle of Affine Transformation, is calculated the binaryzation just put and restores QR code
Image.Wherein affine transformation as shown in figure 5, wherein XN-axis、YN- axis is the coordinate system after conversion, and zero is O'
(0,0), A1'、A'2、A'3、A'4Four angle points for the QR code after conversion.
Step (4.1), according to size in broad image for the QR code, obtains QR code-phase truer QR code in broad image
Amplification, is calculated four angle points of amplification；
Step (4.2), using four obtained in four angle points of the QR code obtaining in step (3.3) and step (4.1)
Angle point, is calculated the linear solution of Homography matrix；
Step (4.3), using Principle of Affine Transformation, is calculated the recovery QR code just put；
Affine transformation is given by：
Wherein H is to use for Homography homography matrix it is known that Homography homography matrix is the invertible matrix of 3*3
Come the projected position to calculate in the point on same three-dimensional planar in different two dimensional images, it is a man-to-man mapping, and H
All there are correct mapping relations for each of input picture point.The linear solution calculating Homography needs 4 to not
Conllinear point.4 pairs of not conllinear points are given by step (3.3) and step (4.1).
According to Principle of Affine Transformation, it is calculated the recovery QR code just put as shown in Figure 6.
Step (5), the recovery just put QR code division is segmented into N*N module, and the QR code of the Class1 that the present embodiment is selected is
21*21 module, as shown in Figure 7.Each module of traversal QR code, calculates institute's average gray a little in each module, if putting down
All gray scale thinks that more than 150 this module is white, otherwise for black.Obtain fuzzy Q R code restoration result as shown in Figure 8.Can
See it compared to other restoration algorithms, obtaining is a QR code close to standard.
Described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Based on the present invention
In embodiment, the every other enforcement that those of ordinary skill in the art are obtained under the premise of not making creative work
Example, broadly falls into the scope of protection of the invention.
Claims (1)
1. a kind of fuzzy Q R code restored method based on affine transformation is it is characterised in that comprise the following steps：
Step（1）, using the constant principle of moment of Hu, in the motion blur image calculating parked, comprise the ROI figure in the region of QR code
Picture；Step includes：
Step（1.1）, using Gaussian image pyramid, downward to motion blur image three times down-sampled；
Step（1.2）, detect the marginal information of down-sampled image downwards, calculate the Hu not bending moment of all marginal informations, according to Hu
Bending moment does not obtain the edge that size meets, as the edge of QR code；
Step（1.3）, comprise step with minimum rectangle（1.2）In the edge that obtains, obtain four angle points of minimum rectangle, respectively
It is multiplied by 3, the minimum obtaining QR code in motion blur image comprises rectangle, and segmentation figure picture obtains ROI image；
Step（2）, with traditional image recovery method to step（1）The ROI image obtaining carries out preliminary motion smear restoration；Step
Rapid inclusion：
Step（2.1）, according to the direction of motion of automatic guided vehicle, obtain the motion blur direction of ROI image；
Step（2.2）, according to the movement velocity of automatic guided vehicle, obtain the motion blur distance of ROI image；
Step（2.3）, using vanishing moment number be 4 db4 wavelet transformation, obtain 4 sub- band images of ROI image, point
Be not low frequency part LL of original image, vertical low frequency part HL of horizontal high-frequent of original image, original image horizontal low frequencies vertically high
Frequency part LH, the diagonal HFS HH of original image；According to step（2.1）, step（2.2）In obtain motion blur direction and fortune
Dynamic fuzzy distance, is restored to LL motion blur using Wiener filtering, using Laplace operator, LH, HL, HH edge is kept；
Step（2.4）, using wavelet inverse transformation, 4 sub- band images are reconstructed the ROI image of recovery；
Step（3）, using run-length encoding, obtain four angle points of QR code in the ROI image restoring, step includes：
Step（3.1）, according to grey level histogram, using Otsu threshold method, the ROI image binaryzation that will restore；
Step（3.2）, using median filter, dispel the salt-pepper noise in binaryzation ROI image and ringing effect；
Step（3.3）, calculate the run-length encoding of binaryzation ROI image, according to the feature of QR code, be calculated binaryzation ROI figure
Four angle points of QR code in picture；
Step（4）, using Homography matrix and Principle of Affine Transformation, it is calculated the binaryzation just put and restores QR code figure
Picture, step includes：
Step（4.1）, according to size in broad image for the QR code, obtain the amplification of QR code-phase truer QR code in broad image
Multiple, is calculated four angle points of amplification；
Step（4.2）, using step（3.3）In four angle points of QR code of obtaining and step（4.1）In four angle points obtaining,
It is calculated the linear solution of Homography matrix；
Step（4.3）, using Principle of Affine Transformation, it is calculated the recovery QR code just put；
Step（5）, the recovery just put QR code division is segmented into N*N module, according to the feature of QR code, travels through N*N module, according to
The feature of each module, current block is entered as black or white.
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| CN107885217A (en) * | 2017-12-14 | 2018-04-06 | 中国计量大学 | Visual guidance method and visual guidance car based on optimal iterations |
| CN107944324A (en) * | 2017-11-16 | 2018-04-20 | 凌云光技术集团有限责任公司 | A kind of Quick Response Code distortion correction method and device |
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| CN112101058A (en) * | 2020-08-17 | 2020-12-18 | 武汉诺必答科技有限公司 | Method and device for automatically identifying test paper bar code |
| CN113468905A (en) * | 2021-07-12 | 2021-10-01 | 深圳思谋信息科技有限公司 | Graphic code identification method and device, computer equipment and storage medium |
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