CN101419668A - Cement pavement image groove removing method based on two-dimension fourier transform - Google Patents

Cement pavement image groove removing method based on two-dimension fourier transform Download PDF

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CN101419668A
CN101419668A CN 200810186635 CN200810186635A CN101419668A CN 101419668 A CN101419668 A CN 101419668A CN 200810186635 CN200810186635 CN 200810186635 CN 200810186635 A CN200810186635 A CN 200810186635A CN 101419668 A CN101419668 A CN 101419668A
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image
pavement
fourier transform
cutting
pavement image
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CN101419668B (en
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潘玉利
赵怀志
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ZHONGGONG HI-TECH CONSERVATION TECHNOLOGY CO LTD
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Abstract

The invention discloses a cement pavement image notch groove removing method based on 2-d Fourier transformation. In the method, a pavement image comprising a notch groove image; the size of an adding window of the Fourier transformation is arranged, and the gray value sequence of the pavement image is obtained; the Fourier transform is implemented on the gray value sequence of the pavement image according to the arranged adding window to obtain a spectrum thereof; the spectral peak of the notch groove is filtered and Fourier inverse transformation is carried out; the filtered image is output. The method in the invention can effectively remove the notch groove in the pavement image, prevent the notch groove image from being misjudged as damaged pavement during the detection process of the pavement and improve the detection accuracy of the pavement.

Description

The method of removing based on the cement pavement image groove of two-dimension fourier transform
Technical field
The present invention relates to technical field of image processing, be meant the method for removing based on the cement pavement image groove of two-dimension fourier transform especially.
Background technology
In the process that road pavement detects, testing process is to handle by ground being carried out image conversion, and the image after handling is discerned, and in identifying, detects damaged road surface; In identifying, can there be the cutting on the road surface in the image, in the pavement image identification of breakage, at first the cutting on road surface is removed, be unlikely to the cutting mistake is identified as the crack, be beneficial to the crack identification in later stage, but present image recognition can not identify cutting, thereby causes judging into cutting by accident crack treatment.
Summary of the invention
In view of this, the invention reside in provides the method for removing based on the cement pavement image groove of two-dimension fourier transform, above-mentioned in the identifying of damaged pavement image to solve, and cutting is judged into by accident the problem of crack treatment.
For addressing the above problem, the invention provides the method for removing based on the cement pavement image groove of two-dimension fourier transform, comprising:
Acquisition comprises the pavement image of cutting image; The windowing size of Fourier transform is set, obtains the gray value sequence of pavement image; According to the windowing that is provided with the gray value sequence of described pavement image is carried out Fourier transform, obtain its frequency spectrum; The spectrum peak of filtering cutting, and inverse fourier transform; Export filtered image.
Preferably, the gray value sequence of described acquisition pavement image comprises:
Obtain corresponding gray value sequence respectively according to the pixel of pavement image and the pixel of cutting image.
Preferably, described windowing according to setting is carried out Fourier transform to the gray value sequence of described pavement image, and the process that obtains its frequency spectrum comprises:
Gray value sequence to cutting image and pavement image is carried out Fourier transform respectively, obtains superposeing behind the frequency spectrum.
Preferably, the spectrum peak of described filtering cutting comprises:
Frequency spectrum after the stack is composed peaks uniformly-spaced to filter 10.
Method of the present invention can effectively be removed the cutting in the pavement image, avoids in the pavement detection process, and the erroneous judgement of cutting image is damaged road surface, improves the accuracy in detection on road surface.
Description of drawings
Fig. 1 is the process flow diagram of the embodiment of the invention.
Embodiment
For clearly demonstrating the scheme among the present invention, provide preferred embodiment below and be described with reference to the accompanying drawings.
Referring to Fig. 1, Fig. 1 is the process flow diagram of the inventive method embodiment, comprising:
Step 11: the pavement image that obtains to comprise the cutting image;
The pavement image that comprises the cutting image that video recording equipment is taken, the cutting image in the pavement image is level of approximation and the straight line that runs through image, and these cuttings are equidistantly arranged, and gray scale is basic identical, therefore has in vertical direction periodically.Unified highway construction standard is followed in the cutting of cement pavement in construction, the width and the spacing of cutting are all fixed, and can calculate cutting width and spacing in the correspondence image in conjunction with the parameter of images acquired equipment.In addition, because cutting interblock space occurrence number with respect to the interior interval of group is less, and has integer relation, and is little to the periodicity influence of integral body, thereby the influence to spectral shape is little, so think that cycle of images is " cutting width and a spacing distance sum " when handling.
Step 12: the windowing size of Fourier transform is set, obtains the gray value sequence of pavement image;
The periodicity of cement cutting pavement image shows on the benchmark vertical direction that establishing the cutting image spacing is s pixel, and the width of cutting image is a t pixel; The gray-scale value of pavement image is A, the gray-scale value B of cutting image-region.So, x 1(n) the pixel grey scale value sequence of expression cutting interval location, i.e. the gray-scale value of pavement image, as the formula (1); x 2(n) the pixel grey scale value sequence of expression cutting position, as the formula (2).X (n) is with x 1(n) and x 2(n) be the sequence of carrying out continuation and brachymemma formation the cycle with M, as the formula (3), its cycle is M=s+t.
x 1 ( n ) = A , n = 0,1 , · · · , s - 1 0 , n = s , s + 1 , · · · , N - 1 - - - ( 1 )
Figure A200810186635D00052
x ( n ) = x 1 T ( n ) + x 2 T ( n ) , n = 0,1 , · · · N - 1 - - - ( 3 )
Wherein x 1 T ( n ) = Σ l 1 x 1 ( n - l 1 M ) , x 2 T ( n ) = Σ l 2 x 2 ( n - l 2 M ) , N is the width of rectangular window in the brachymemma process, l 1And l 2Be respectively sequence x 1(n) and x 2(n) number in the brachymemma scope.
Step 13: according to the windowing that is provided with the gray value sequence of described pavement image is carried out Fourier transform, obtain its frequency spectrum;
To sequence x 1(n) and x 2(n) do respectively that leaf transformation obtains X in the N point discrete Fourier 1(k) and X 2(k),
Figure A200810186635D00056
With
Figure A200810186635D00057
Be respectively x 1(n) and x 2(n) with M be the result who the cycle carries out continuation and brachymemma, be the stack after the ring shift,, can obtain leaf transformation X (k) in the N point discrete Fourier of sequence x (n) therefore according to the time-domain cyclic shift character of discrete Fourier transformation, and then obtain the amplitude spectrum of x (n), as the formula (4).
| X ( k ) | = | x 1 T ( k ) + X 2 T ( k ) |
= | A sin ( π N ks ) sin ( π N k ) e - j π N k ( s - 1 ) Σ l 1 e - j 2 π N kl 1 M + B sin ( π N kt ) sin ( π N k ) e - j π N k ( s + M - 1 ) Σ l i e - j 2 π N kl 2 M |
= 1 | sin ( π N k ) | | A sin ( π N ks ) · Σ l 1 e - j 2 π N kl 1 M + B sin ( π N kt ) · e - j π N kM Σ l 1 e - j 2 π N kl 2 M |
(k=0,1,…,N-1) (4)
In the cutting cement pavement, M is far smaller than the number of pixels on the image vertical direction, that is to say in sequence x (n), and M is far smaller than the rectangular window width (N) that is used for the sequence brachymemma, and according to the natural quality of cutting, the cutting number in the image is with number is basic identical at interval.In order to handle conveniently, when the qualitative analysis of spectral characteristic, might as well establish l 1=l 2, formula (4) can be transformed to formula (5) so.
| X ( k ) | = | x 1 T ( k ) + X 2 T ( k ) |
= | Σ l 1 e - j 2 π N kl 1 M sin ( π N k ) | | A sin ( π N ks ) + B sin ( π N kt ) · e - j π N kM |
(k=0,1,…,N-1) (5)
Formula (5) has reflected the frequency domain characteristic of sequence x (n), works as in the formula
Figure A200810186635D00066
In every value be at 1 o'clock | X (k) | value bigger, tangible spectrum peak is arranged, the position of therefore composing the peak is k=[N/M] and frequency multiplication place.
Step 14: eliminate the spectrum peak of cutting, and inverse fourier transform;
When eliminating the spectrum peak, adopt 10 spectrums of uniformly-spaced filtering peak the best, and the frequency spectrum sequence that will eliminate behind the spectrum peak is carried out inverse fourier transform.
Step 15: export filtered image.
Have only pavement image in the filtered image, eliminated cutting.
Method of the present invention can effectively be removed the cutting in the pavement image, avoids in the pavement detection process, and the erroneous judgement of cutting image is damaged road surface, improves the accuracy in detection on road surface.
For the method for being set forth among each embodiment of the present invention, within the spirit and principles in the present invention all, any modification of being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (4)

1, the method for removing based on the cement pavement image groove of two-dimension fourier transform is characterized in that, comprising:
Acquisition comprises the pavement image of cutting image; The windowing size of Fourier transform is set, obtains the gray value sequence of pavement image; According to the windowing that is provided with the gray value sequence of described pavement image is carried out Fourier transform, obtain its frequency spectrum; The spectrum peak of filtering cutting, and inverse fourier transform; Export filtered image.
2, method according to claim 1 is characterized in that, the gray value sequence of described acquisition pavement image comprises:
Obtain corresponding gray value sequence respectively according to the pixel of pavement image and the pixel of cutting image.
3, method according to claim 2 is characterized in that, described windowing according to setting is carried out Fourier transform to the gray value sequence of described pavement image, and the process that obtains its frequency spectrum comprises:
Gray value sequence to cutting image and pavement image is carried out Fourier transform respectively, obtains superposeing behind the frequency spectrum.
4, method according to claim 3 is characterized in that, the spectrum peak of described filtering cutting comprises:
Frequency spectrum after the stack is composed peaks uniformly-spaced to filter 10.
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101814138A (en) * 2010-04-09 2010-08-25 同济大学 Method for identifying and classifying types of damage of sealants of cement concrete pavement based on images
CN104101601A (en) * 2014-06-23 2014-10-15 深圳市大族激光科技股份有限公司 Detection device and method for surface defects
CN106530223A (en) * 2016-11-28 2017-03-22 清华大学 Fast Fourier ghost imaging method and system based on frequency domain modulation
CN107665279A (en) * 2017-09-26 2018-02-06 福建农林大学 Road face cutting automatic identifying method

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101814138A (en) * 2010-04-09 2010-08-25 同济大学 Method for identifying and classifying types of damage of sealants of cement concrete pavement based on images
CN101814138B (en) * 2010-04-09 2013-10-30 同济大学 Method for identifying and classifying types of damage of sealants of cement concrete pavement based on images
CN104101601A (en) * 2014-06-23 2014-10-15 深圳市大族激光科技股份有限公司 Detection device and method for surface defects
CN106530223A (en) * 2016-11-28 2017-03-22 清华大学 Fast Fourier ghost imaging method and system based on frequency domain modulation
CN106530223B (en) * 2016-11-28 2020-01-10 清华大学 Fast Fourier ghost imaging method and system based on frequency domain modulation
CN107665279A (en) * 2017-09-26 2018-02-06 福建农林大学 Road face cutting automatic identifying method

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