CN100380393C - Precise location method of QR code image symbol region at complex background - Google Patents

Precise location method of QR code image symbol region at complex background Download PDF

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CN100380393C
CN100380393C CNB2006101133792A CN200610113379A CN100380393C CN 100380393 C CN100380393 C CN 100380393C CN B2006101133792 A CNB2006101133792 A CN B2006101133792A CN 200610113379 A CN200610113379 A CN 200610113379A CN 100380393 C CN100380393 C CN 100380393C
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sign indicating
indicating number
image
quadrilateral
summits
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CN1924899A (en
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明安龙
马华东
刘德宇
胡自强
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Fujian Rongji Software Co., Ltd.
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FUJIAN RONGJI SOFTWARE DEVELOPMENT Co Ltd
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Abstract

This invention relates to accurate position method under complex background of QR codes image area, which comprises the following steps: a, adopting self-adapting valve binary method to filter focus out effect and fringe information of each module and keep central information; b, finding out the said QR codes image outline through outer fringe an finding out all position detection image according to detected image characteristics; c, processing rotation test on the said image to determine their normal QR codes image relative position; d, determining its QR code image area according to the said position detection image.

Description

The accurate positioning method in QR sign indicating number pictorial symbol zone under the complex background
Technical field
The present invention relates to a kind of image processing method of two-dimensional bar code, especially a kind of accurate positioning method at QR sign indicating number pictorial symbol zone under the complex background belongs to technical field of image processing.
Background technology
The QR sign indicating number, the fast answer code of expressing one's gratification again is a kind of matrix two-dimensional code symbol, for numeral, letter, encode Chinese characters for computer specific compact model is arranged.The QR sign indicating number has characteristics such as high power capacity, high density, error correcting capability are strong, security intensity height, is widely used in various fields such as authentication, safety anti-fake, ecommerce.GB GB/T 18284-2000 has put down in writing the standard of QR sign indicating number.As shown in Figure 1, the rectangular array symbol (rectangular array symbol region is decided to be symbol area approximately) that the QR sign indicating number is made up of the square modules (being referred to as module later on) of a series of dark colors and light color is divided into two parts of functional graphic and coding region.Wherein, functional graphic comprises: the position sensing figure, be also referred to as the view finding figure, and be three identical square symbol that lay respectively at the upper left corner, the upper right corner and the lower left corner of matrix notation, the length of side of each view finding figure is 7 modules; Be used for determining one of the matrix notation position fixedly figure, i.e. correction graph; The positioning pattern that is used for the coordinate of definite symbol module.Coding region comprises at least: data and error correction character code; Be used for format information that the remainder of coding region is deciphered.
The conventional method of two-dimensional bar code identification is earlier bar code image to be carried out first order difference, finds out the boundary position of bar code image.But, behind the optical system imaging that uses no automatic focusing, such as using mobile phone photograph, it is fuzzy unusually that bar code border will become, and boundary portion branch mutual superposition and skew, as shown in Figure 2, add influence of environmental noise, traditional bar code recognition will be no longer suitable.
Application for a patent for invention CN1818926 discloses a kind of pinpoint method in two-dimension code zone that is used for two-dimension code identification:
(1) the colored bitmap-converted with the two-dimension code to be identified gathered is 256 color shade bitmaps;
(2) set a threshold value, with the gray-scale value and the threshold of each pixel of above-mentioned gray bitmap, if greater than threshold value, then assignment 1, if less than threshold value, then assignment 0, obtains binary image, and threshold value be less than 255 positive integer greater than zero;
(3) respectively to X-axis, the Y-axis projection of above-mentioned binary image, write down X value, the Y value in jump frequency highest region territory, with this X, the combination of Y value is as the central point in two-dimension code zone;
(4) be starting point from above-mentioned central point, up and down, left and right four direction scans successively, when light areas and darker regions generation saltus step, and the cumulative length of light areas is during less than a length threshold, finish scanning, obtain four original outermost point in two-dimension code zone;
(5) be that starting point is according to counterclockwise or clockwise direction with above-mentioned any one original outermost point, press its excess-three point of track process of the square box of above-mentioned four outermost point formation, get back to starting point at last, scan, if one side of outermost point of process light areas and darker regions generation saltus step are arranged, then this outermost point is moved to the binary image edge by a fixed step size, obtain a new outermost point, and substitute corresponding original outermost point with this new outermost point;
(6) being more arbitrarily starting point in above-mentioned original outermost point and the new outermost point, repeating step (5), all there is not saltus step between light areas and the darker regions until every limit of described square box, obtain four last outermost point, the square box that is formed by these four last outermost point is the zone of two-dimension code.
Another document (is seen Eisaku Ohbuchi etc., Barcode Readers using the Camera Device inMobile Phones.Proceedings of the 2004 International Conference on Cyberworlds, 2004.) another kind of method has been described, as shown in Figure 3:
1. calculate the center of gravity of the image that is taken, be made as (x c, y c);
2. carry out the scanning of 8 directions from outside to inside, promptly be parallel to four edges and cornerwise 8 scanning directions of figure below rectangular area, stop up to the edge that scans symbol area;
3. if more than one of the pixel of the symbol area when stopping on the sweep trace is then selected a marginal point;
4. can obtain maximum 16 marginal points through overscanning;
5.16 the nearest marginal point of individual marginal point middle distance pixel (0,0) is a summit of a symbol area;
6. defining vectorial P is (x 0, y 0)-(x c, y c).
7. calculate inner product find symbol area other summit.
But there is significant deficiency in said method:
1, under the complex background of practical application, the method for scanning marginal point will be no longer suitable, and this is quite obvious, as shown in Figure 4, its reason is to have a lot of noise spots under the complex background, and sweep trace can't be distinguished noise spot and whether belong to symbol area, thus the location mistake.
2, always there are not 4 summits in QR sign indicating number pictorial symbol zone, and as shown in Figure 5, sweep trace scans 5 outermost point (5 dots among the figure), and as can be seen, Ding Wei symbol area has just been lost the information of some light modules in view of the above.
When 3, actual photographed QR sign indicating number picture is discerned, may be because the relation of shooting angle causes symbol area that bigger rotation takes place, at this moment we will judge that each summit corresponds to the position in normal QR sign indicating number pictorial symbol zone, it is rotation type, but said method can only the sprocket bit zone, can not judge rotation type.
Summary of the invention
At the problems referred to above, the object of the present invention is to provide the accurate positioning method in QR sign indicating number pictorial symbol zone under a kind of complex background.Technical matters to be solved is:
1, handles defocusing blurring QR sign indicating number image, as mobile phone picture shot that can't automatic focusing;
2, QR sign indicating number pictorial symbol zone, location under complex background;
3, judge rotation type;
4, calculate QR sign indicating number version.
Of the present invention being contemplated that: at first adopt the method for adaptive threshold binaryzation directly to remove the module edge information that causes owing to the defocusing blurring effect, keep the information of all module centers; Then utilize the external margin profile to search algorithm and detect three view finding figure/position sensing figures that are positioned at QR sign indicating number image vertex position, and 12 summits of definite these three view finding figures, and then just can judge rotation type and accurately locate whole QR sign indicating number pictorial symbol zone.Under the complex background of practical application, this method can directly detect all position sensing figures, overcomes the interference of picture noise, obtains high success ratio and precision.The algorithm complex of this method is low relatively, can guarantee harmless the filtration substantially, and requirement of real time.
According to above-mentioned design, the present invention mainly comprises following four steps:
1, filtering defocusing blurring effect
The matrix notation that QR sign indicating number image is made up of a series of dark colors and light square modules, according to as can be known to the common practise of out-of-focus image, for each module in the matrix, regardless of the degree of defocusing blurring effect, the projection on the plane behind its defocusing blurring must be the distortion of this square modules.If the angle of taking is perpendicular to the QR sign indicating number plane of delineation, the distortion of square modules should be approximate (for example being deformed into a circle) uniformly on all directions so, and promptly the color at center is constant.If the angle of taking is not perpendicular to the QR sign indicating number plane of delineation, also can revert to vertical situation by anti-perspective transform; Simultaneously, the fuzzy edge that mainly concentrates on square modules of out-of-focus image.Therefore, can adopt the method for adaptive threshold binaryzation directly to remove marginal information, keep the information of module centers.
The adaptive threshold binaryzation adopts the class techniques of discriminant analysis to determine threshold value, and the image that the threshold value that adopts this method to obtain is carried out binaryzation has good background and prospect stalling characteristic.Convert coloured image to gray-scale map, the gradation of image value is from 0 like this ... 255 change.If S i(i=0 ... 255) the interior gray scale of expression QR sign indicating number image is from 0 ... 255 pixel number, i.e. probability histogram, T iThe expression threshold value, threshold value is divided into two class C with the gray scale of image 0∈ [O, T i], C 1∈ [T i+ 1,255], correspond respectively to background and QR sign indicating number pictorial symbol zone, this two inter-class variance should be maximum, and corresponding two inter-class variances are minimum.Because the inner variance sum of the inter-class variance of a sub-picture and class is a constant, therefore only need to determine threshold value T again according to the maximum variance between class iBe the method for from image, extracting threshold values automatically below:
1) image histogram is carried out normalization:
Σ i = 0 255 p i = 1 p i = n i N P i ≥ 0 Σ i = 0 255 p i = 1
Wherein, N is the image number of total picture element, n iFor gray scale is the number of picture elements of i, then C 0, C 1Probability and average that type occurs are as follows:
W 0 = p r ( C 0 ) = Σ i = 0 i p i = w ( t ) W 1 = p r ( C 1 ) = Σ i = t + 1 255 p i = 1 - w ( t )
u 0 = Σ i = 0 i ip i w 0 = u ( t ) w ( t ) u 1 = Σ i = t + 1 255 ip i w 1 = u r - u ( t ) 1 - w ( t )
Wherein u r = Σ i = 0 255 ip i Be the average of QR sign indicating number image, C 0, C 1The inter-class variance of class is
σ B 2 = w 0 ( u 0 - u r ) 2 + w 1 ( u 1 - u r ) 2 = w 0 w 1 ( u 1 - u 0 ) 2
2) ask optimal threshold t *Should make the inter-class variance maximum, promptly
t * = arg max σ B 2 ( 0 ≤ r ≤ 255 )
The specific implementation method is as follows:
1) finds out the minimum and maximum gray-scale value of image earlier,, regard threshold values as, the gray-scale value of image is divided into two classes for each gray-scale value between the minimum and maximum gray-scale value.
2) calculate two inter-class variances one by one and deposit in the one dimension variance array, be designated as the current gray-scale value of cutting apart down.
3) for the variance array, search maximum variance yields, its subscript is the threshold values T that we ask iBy the filtering gray-scale value greater than this threshold values T iInformation, we can the obtain filtering QR sign indicating number image of defocusing blurring effect.
2. search the view finding figure:
Obtain comparatively clearly after the QR sign indicating number image, just the further zone of this image of Search and Orientation.The target of searching is three the view finding figures (upper left corner, the upper right corner and the lower left corner) that are positioned at QR sign indicating number matrix notation vertex position, and the method for searching is to utilize the external margin profile to search 12 summits that algorithm detects these three view finding figures.
There are a lot of technology can realize the detection of inside or exterior contour, Suzuki and Abe Suzuki (Topoiogicalstructural analysis of digital binary images by border following.CVGIP, vol.30,1985.) a kind of exterior contour detection algorithm proposed, this algorithm is based on the notion of profile in abutting connection with tree, can distinguish and from the cavity, be partitioned into a series of assemblies (annotate: background is around assembly, assembly may comprise the cavity, and the cavity also may comprise other object conversely), wherein profile is in abutting connection with tree, assembly, notions such as cavity are the key concept of digital topology, see Kong T.Y.and Rosenfeld A., Digital Topoiogy:Introduction and Survey, CVGIP, Vol.48,1989, pp.357-393).The present invention is considered as the cavity with three view finding figures in the QR sign indicating number image, uses this exterior contour detection algorithm to detect all outside quadrilaterals, adds the filtration of quadrilateral concavity and angle then, can orient 12 summits of view finding figure apace:
1) utilize described exterior contour detection algorithm that input picture is detected, and all exterior contours that will detect are kept in the chained list;
2) to each profile in this chained list, filtering successively through the following steps:
A. if this profile contains four summits, illustrate that this profile is a quadrilateral, then continue, otherwise give up;
B. if this tetragonal concavity and convexity is protruding, then continues, otherwise give up;
C. belong to interval [a, b] as if this tetragonal interior angle and then continue, otherwise give up.
Wherein, [a, b] defines tetragonal interior angle angle between inner corner region, 0 °＞a＞180 ° and 0 °＞b＞180 °.Those skilled in the art will appreciate that rule of thumb to be worth between this inner corner region to determine, in embodiments of the present invention, preferably elect [70 °, 120 °] between this inner corner region as.By above-mentioned steps, just can obtain comprising the some tetragonal set of three view finding figures.
3), can think that then these three quadrilaterals are exactly the view finding figure that will search if having only three quadrilaterals in this set; If the quadrilateral number in should gathering then also needs wherein other quadrilaterals except that the view finding figure of further filtering more than three.
The method of filtering is to judge by following two conditions: the one, and tetragonal area can not surpass 1/9 of QR sign indicating number image area, the 2nd, the tetragonal length of side about equally, because the view finding figure itself is the quadrilateral that the length of side equates, even produce distortion owing to the perspective distortion distortion or owing to rotation makes image, but according to the perspective transform principle, the length of side of its distortion or fault image also should be about equally.According to above two conditions, can from above-mentioned quadrilateral set, determine three view finding figures exactly:
I) at first travel through all quadrilaterals, find out minimum and maximum x coordinate, and minimum and maximum y coordinate, obtain the approximate area of QR sign indicating number image-region;
Ii), calculate its area according to Helen's triangle area computing formula and deposit an array S[in for each quadrilateral]:
At first scanning obtain certain tetragonal three summit, calculate respectively between these three summits apart from a, b, c;
Make p=(a+b+c)/2;
Drawing these 3 the leg-of-mutton areas of composition is:
S1＝sqrt(p*(p-a)*(p-b)*(p-c))；
In like manner can be in the hope of the leg-of-mutton area S2 of another except that this triangle in this quadrilateral.Two triangle area sum S=S1+S2 are this tetragonal area;
Iii) the filtering area is greater than 1/9 quadrilateral of the approximate area in QR sign indicating number pictorial symbol zone;
The quadrilateral of iv) finding out the area maximum is as first view finding figure.Obtain this tetragonal central point, travel through remaining quadrilateral, comprise this central point, represent then that it is relevant with first view finding image if having in other quadrilateral, so by filtering;
V) repeating step 4) twice, find out second and the 3rd view finding figure.
By said method, 12 summits of these three view finding figures that can measure with considerable accuracy.
In addition, for speed and the precision that improves the exterior contour detection algorithm, we can carry out rim detection to image in advance, can use various operators during detection, preferably can select the Canny operator.
3, judge rotation type:
These three view finding figures are rotated detection just can draw rotation type, concrete steps are:
1), the center of three view finding figures is linked to each other obtains a triangle;
2), asking this longest limit of triangle length of side, its relative triangular apex is the central point of QR sign indicating number pictorial symbol zone upper left corner view finding figure;
3), be the center with this central point, counterclockwise observe two other summits of this triangle, first summit that runs into is the central point of QR sign indicating number pictorial symbol zone lower left corner view finding figure, the another one summit then is the central point of upper right corner view finding figure.
We just obtain three detected view finding figures corresponding position in normal QR sign indicating number pictorial symbol zone like this.
4. accurately locate QR sign indicating number pictorial symbol zone:
After obtaining the position of three detected view finding figures correspondence in normal QR sign indicating number pictorial symbol zone, we just can accurately locate QR sign indicating number pictorial symbol zone by following method, as shown in Figure 6:
1) in four summits, chooses a summit, be made as P corresponding to the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone 1, the distance of the central point of this summit and other two view finding figures in these four summits farthest;
2) in four summits, choose two summits, be made as P corresponding to the view finding figure in the lower left corner, normal QR sign indicating number pictorial symbol zone 4And P 41, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
3) in four summits, choose two summits, be made as P corresponding to the view finding figure in the upper right corner, normal QR sign indicating number pictorial symbol zone 2Point and P 21, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
4) cross some P respectively 1And P 2, P 1And P 4, P 2And P 21, P 4And P 41Make four straight lines, these four folded zones of straight line are QR sign indicating number pictorial symbol zone.
Technique effect of the present invention is:
1, adopt the adaptive threshold binaryzation to carry out defocusing blurring and filter, reach following effect:
1) take apparatus and have nothing to do, picture is irrelevant.
2) algorithm complex is low relatively, can guarantee harmless the filtration substantially.
3) requirement of real time.
2, under the complex background of practical application, adopt exterior contour detection algorithm jointing edge to detect and locate the view finding figure, reach following effect:
1) because complex background in interference mostly be assorted point, hardly may with three view finding image similarities, so the present invention directly detects view finding figure rather than analyzing spot, obtain high success ratio and precision like this;
2) need not to consider the detected rotation of QR sign indicating number pictorial symbol zone in the space, can judge the rotation type in QR sign indicating number pictorial symbol zone on the contrary according to testing result;
3) according to QR sign indicating number coding rule, the length of side of the square-shaped frame of three view finding figures is 7 modules, therefore, can directly obtain the version number of current QR sign indicating number image under a proportional relationship, what modules are the length of side that is symbol area be, removed the complicated calculations of asking version number like this from, and the accuracy of the version number that obtains like this is very high;
What 4) use is ripe algorithm general in the Flame Image Process, and complexity is low and can control.
Description of drawings
Fig. 1 is the structural representation of QR sign indicating number;
Fig. 2 represents the blurred picture of QR sign indicating number;
Fig. 3 represents to utilize in the prior art method that scans marginal point to determine the method synoptic diagram of QR sign indicating number image-region;
Fig. 4 represents the synoptic diagram of QR sign indicating number image under the complex background;
Fig. 5 represents to utilize the lead to errors synoptic diagram of location of the method for scanning marginal point;
Fig. 6 represents accurately to locate the position fixing process synoptic diagram of QR sign indicating number image-region;
Fig. 7 is illustrated in the most preferred embodiment of the present invention, and Fig. 2 is adopted effect after the adaptive threshold binarization method filtering defocusing blurring effect:
Fig. 8 is illustrated in three the view finding figures that most preferred embodiment of the present invention finds out and the synoptic diagram on 12 summits thereof;
Fig. 9 represents the accurate positioning result of most preferred embodiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing, be described in detail the accurate location of how to realize QR sign indicating number image-region under the complex background.
Looking like with QR sign indicating number shown in Figure 2 is example, and most preferred embodiment of the present invention is implemented as follows:
1. adaptive threshold binarization method filtering defocusing blurring effect:
Colored QR sign indicating number image transitions is become gray-scale map, find out the minimum and maximum gray-scale value T of image respectively MaixAnd T Min, for each the gray-scale value T between the minimum and maximum gray-scale value i, all be seen as threshold value, and according to T iThe gray-scale value of image is divided into greater than T iWith less than T iTwo classes.At each gray-scale value T i, the variance of calculating one by one between two classes deposits in the one dimension variance array.Search the maximum variance value in this variance array, its corresponding gray scale value is exactly the optimal threshold T that is used for filtering defocusing blurring effect.By the information of filtering gray-scale value greater than this threshold value, the sign indicating number of the QR clearly image of defocusing blurring effect that just obtained filtering, as shown in Figure 7, the effect behind the defocusing blurring that has been exactly filtering.
2. search the view finding figure:
(1) image is carried out rim detection, uses the Canny operator in this example:
(2) utilize the exterior contour detection algorithm that input picture is detected, and all exterior contours that will detect are kept in the chained list;
(3) to each profile in this chained list, filtering successively through the following steps:
A. if this profile contains four summits, illustrate that this profile is a quadrilateral, then continue, otherwise give up;
B. if this tetragonal concavity and convexity is protruding, then continues, otherwise give up;
C. belong to interval [70 °, 120 °] as if this tetragonal interior angle and then continue, otherwise give up.
The specific implementation algorithm of said method is expressed as follows:
Find3Squares (X) //the X representing input images
begin
Define a list m_Contours=NULL//chained list of definition writes down profile
Find?extreme?outer?contours?in?X?using?the?algorithm?described?in[3]and?return
them?to?m_Contours：
Define a list m_Squares=NULL//chained list of definition is preserved 3 position sensing figures
while(m_Contours?！＝NULL)
{
If (m_Contours-＞first has 4 vertex) if // first profile of chained list comprises four summits
{
If (the convexi ty of m_Contours-＞first is true) if // first profile of chained list recessed
Convexity is protruding
{
The maximum interior angle of max=the maximum angle of m_Contours-＞first//ask
The minimum interior angle of min=the minimum angle of m_Contours-＞first//ask
if((max_angle＜120)and(min_algle＞70))
Add m_Contours to m_Squares//qualified profile is added the quadrilateral chained list
}
}
M_Contours=m_Contours-＞next//forward to next one
}
Return m_Squares returns the west shape chained list of trying to achieve
end
(4), can think that then these three quadrilaterals are exactly the view finding figure that will search if having only three quadrilaterals in this set; If the quadrilateral number in should gathering then also needs wherein other quadrilaterals except that the view finding figure of further filtering more than three:
I) at first travel through all quadrilaterals, find out minimum and maximum x coordinate, and minimum and maximum y coordinate, obtain the approximate area of QR sign indicating number image-region;
Ii), calculate its area according to Helen's triangle area computing formula and deposit an array S[in for each quadrilateral]:
At first scanning obtain certain tetragonal three summit, calculate respectively between these three summits apart from a, b, c;
Make p=(a+b+c)/2;
Drawing these 3 the leg-of-mutton areas of composition is:
S1＝sqrt(p*(p-a)*(p-b)*(p-c))；
In like manner can be in the hope of the leg-of-mutton area S2 of another except that this triangle in this quadrilateral.Two triangle area sum S=S1+S2 are this tetragonal area;
Iii) the filtering area is greater than 1/9 quadrilateral of the approximate area of QR sign indicating number image-region;
The quadrilateral of iv) finding out the area maximum is as first view finding figure.Obtain this tetragonal central point, travel through remaining quadrilateral, comprise this central point, represent then that it is relevant with first view finding image if having in other quadrilateral, so by filtering;
V) in the quadrilateral set of remainder, find out the quadrilateral of area maximum as second view finding image.Same filtering and second quadrilateral that the view finding image is relevant;
Vii) in the quadrilateral set of remainder, find out the quadrilateral of area maximum as the 3rd view finding image.
By said method, 12 summits of these three view finding figures that can measure with considerable accuracy, as shown in Figure 8, wherein, 12 summits of three view finding figures are represented with circle.
3. judgement rotation type
We can draw rotation type by these three view finding figures:
(1), the central point of three view finding figures is linked to each other obtains a triangle;
(2), asking this longest limit of triangle length of side, its relative triangular apex is the central point of QR sign indicating number pictorial symbol zone upper left corner view finding figure;
(3), be the center with the longest pairing summit, limit of this triangle length of side, counterclockwise observe two other summits of this triangle, first summit that runs into is the central point of QR sign indicating number pictorial symbol zone lower left corner view finding figure, and the another one summit is the central point of QR sign indicating number pictorial symbol zone upper right corner view finding figure.
We just obtain three detected view finding figures corresponding position in normal QR sign indicating number pictorial symbol zone like this.
4. accurately locate QR sign indicating number pictorial symbol zone
After obtaining the position of three detected view finding figures correspondence in normal QR sign indicating number pictorial symbol zone, we just can accurately locate QR sign indicating number pictorial symbol zone by following method, as shown in Figure 9:
1) in four summits, chooses a summit, be made as P corresponding to the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone 1, the distance of the central point of this summit and other two view finding figures in these four summits farthest;
2) in four summits, choose two summits, be made as P corresponding to the view finding figure in the lower left corner, normal QR sign indicating number pictorial symbol zone 4And P 41, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
3) in four summits, choose two summits, be made as P corresponding to the view finding figure in the upper right corner, normal QR sign indicating number pictorial symbol zone 2Point and P 21, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
4) cross some P respectively 1And P 2, P 1And P 1, P 2And P 21, P 4And P 41Make four straight lines, these four folded zones of straight line are QR sign indicating number pictorial symbol zone, as shown in Figure 9.

Claims (4)

1. the accurate positioning method in QR sign indicating number pictorial symbol zone under the complex background comprises step:
1) adopt the defocusing blurring effect of the method filtering QR sign indicating number image of adaptive threshold binaryzation, remove the marginal information of each module, keep the central information of each module, the method for described adaptive threshold binaryzation comprises:
11) find out the minimum and maximum gray-scale value T of QR sign indicating number image MaxAnd T Min
12) for each the gray-scale value T between the minimum and maximum gray-scale value i, all be seen as threshold value, and according to T iThe gray-scale value of image is divided into greater than T iWith less than T iTwo classes;
13) at each gray-scale value T i, the variance of calculating one by one between two classes deposits in the one dimension variance array;
14) search maximum variance value in this variance array, its corresponding gray scale value is exactly the optimal threshold T that is used for filtering defocusing blurring effect;
15) the filtering gray-scale value is greater than the information of this threshold value, the QR sign indicating number image of defocusing blurring effect that obtained filtering;
2) search algorithm by the external margin profile and find out exterior contour in the described QR sign indicating number image, and therefrom find out all position sensing figures according to detected image characteristics, wherein, the step that finds out the position sensing figure from exterior contour is:
21) if this profile contains four summits, illustrate that this profile is a quadrilateral, then continue, otherwise give up;
22), then continue, otherwise give up if this tetragonal concavity and convexity is protruding;
23) if this tetragonal interior angle belongs to interval [a, b], then continuation, otherwise give up, wherein, 0 °＞a＞180 ° and 0 °＞b＞180 °;
3) described position sensing figure is rotated detection, determines their corresponding positions in normal QR sign indicating number pictorial symbol zone, wherein, the step that the position sensing figure is rotated detection is as follows:
31) central point of three position sensing figures is linked to each other obtain a triangle;
32) ask this longest limit of triangle length of side, its relative triangular apex is the central point of the upper left corner, QR sign indicating number pictorial symbol zone position sensing figure;
33) be the center with the longest pairing summit, limit of this triangle length of side, counterclockwise observe two other summits of this triangle, first summit that runs into is the central point of the lower left corner, QR sign indicating number pictorial symbol zone position sensing figure, and the another one summit is the central point of the upper right corner, QR sign indicating number pictorial symbol zone position sensing figure;
4) determine the symbol area of the QR sign indicating number image at its place according to described position sensing figure, comprise the steps:
41) in four summits, choose a summit, be made as P corresponding to the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone 1, the distance of the central point of this summit and other two view finding figures in these four summits farthest;
42) in four summits, choose two summits, be made as P corresponding to the view finding figure in the lower left corner, normal QR sign indicating number pictorial symbol zone 4And P 41, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
43) in four summits, choose two summits, be made as P corresponding to the view finding figure in the upper right corner, normal QR sign indicating number pictorial symbol zone 2Point and P 21, this summit and distance corresponding to the central point of the view finding figure in the upper left corner, normal QR sign indicating number pictorial symbol zone are respectively farthest and time far away in these four summits;
44) cross some P respectively 1And P 2, P 1And P 4, P 2And P 21, P 4And P 41Make four straight lines, these four folded zones of straight line are QR sign indicating number pictorial symbol zone.
2. the method for claim 1 is characterized in that, is [70 °, 120 °] between described inner corner region.
3. method as claimed in claim 1 or 2 is characterized in that, also comprises step:
24) travel through all quadrilaterals, find out minimum and maximum x coordinate, and minimum and maximum y coordinate, obtain the approximate area of QR sign indicating number image-region;
25), calculate its area according to Helen's triangle area computing formula for each quadrilateral;
26) the filtering area is greater than step 24) 1/9 quadrilateral of the approximate area of the QR sign indicating number image-region that obtains.
4. method as claimed in claim 3 is characterized in that, also comprises step:
27) find out the quadrilateral of area maximum as first position sensing figure.Obtain this tetragonal central point, travel through remaining quadrilateral, comprise this central point, represent then that it is relevant with first view finding image if having in other quadrilateral, so by filtering;
28) quadrilateral of finding out the area maximum in the set of the quadrilateral of remainder is as second view finding image, same filtering and second quadrilateral that the view finding image is relevant;
29) in the quadrilateral set of remainder, find out the quadrilateral of area maximum as the 3rd view finding image.
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