CN110188582B - Method for identifying locating point in invisible graph code on commodity label - Google Patents
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K19/00—Record carriers for use with machines and with at least a part designed to carry digital markings
- G06K19/06—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
- G06K19/06009—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking
- G06K19/06037—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking multi-dimensional coding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K19/00—Record carriers for use with machines and with at least a part designed to carry digital markings
- G06K19/06—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
- G06K19/06009—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking
- G06K19/06046—Constructional details
- G06K19/06178—Constructional details the marking having a feature size being smaller than can be seen by the unaided human eye
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
- G06K7/1443—Methods for optical code recognition including a method step for retrieval of the optical code locating of the code in an image
Abstract
The invention discloses a method for identifying a locating point in an invisible graph code on a commodity label, which comprises the following steps: step 1: carrying out invisible graphic coding on the label contained information, and embedding positioning points in the original invisible graphic coded image; step 2: printing an invisible graphic coding image containing a positioning point on a label printing medium; and step 3: shooting a printed coded image; and 4, step 4: carrying out binarization and black-and-white morphological processing on the shot image; and 5: identifying embedded positioning points from the preprocessed image according to different areas of the data points and the positioning point communication components, and calculating corresponding positioning point coordinates by using a centroid method; step 6: and determining the corresponding relation of the positioning points according to a triangular positioning identification principle, and carrying out image positioning and geometric transformation. The invention can quickly and accurately calculate the coordinates of the positioning points; the deformation robustness to the commodity label is good, and the anti-interference capability is strong; in the printing of the commodity label, the label cannot be seen by naked eyes, so that the invisible and anti-counterfeiting capability is strong.
Description
Technical Field
The invention relates to a method for identifying a positioning point in an invisible graph code on a commodity label, belonging to the technical field of invisible graph codes.
Background
The anti-counterfeiting of commodities is an important aspect in the current commodity circulation, and manufacturers of counterfeit commodities cause great damage to the benefits of manufacturers and consumers of genuine commodities. Therefore, merchants want to embed anti-counterfeiting codes of invisible graphic codes in their own merchandise labels, wherein the anti-counterfeiting codes include corresponding manufacturer information, product-related information and the like. The invisibility does not interfere with the overall sense of the color, layout and the like of the label original image, and the corresponding coded image is invisible to the naked eye. The graphic coding is to design a coding rule by itself to carry out the graphic coding on the numbers and the symbols, thereby realizing the anti-counterfeiting. The positioning and matching of images is a very important step in invisible image coding.
The invisible image coding technology is a coding technology which uses some figures to code numbers and symbols and can print coded images invisible to naked eyes on media by using a printer, a printer and the like. The invisible graphic code has the advantages of small information bit, large information hiding amount, high safety, low cost, good robustness, strong attack resistance and the like, and plays an increasingly important role in information hiding and anti-counterfeiting. The current invisible pattern codes mainly have two categories, one is a coding and positioning mode based on two-dimensional codes, and the other is a coding and positioning mode which utilizes complex geometric patterns to express data information and positioning information.
In encoding and positioning based on QR two-dimensional codes, image positioning is mainly completed by hough transformation, morphological methods and the like. The existing various image positioning methods have large calculated amount and complex method, and are not beneficial to quick positioning. In the technology of encoding data by complex graphics, the method is sensitive to deformation such as distortion and inclination, has large calculation amount and complex calculation, and is not beneficial to quick positioning and decoding.
Disclosure of Invention
Aiming at the defects of the prior art of invisible graphic codes in commodity anti-counterfeiting labels, the invention aims to provide a method for identifying a positioning point in the invisible graphic codes on the commodity labels by combining corresponding graphic coding rules.
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention discloses a method for identifying a locating point in an invisible graph code on a commodity label, which comprises the following steps of:
step 1: carrying out invisible image coding on the content contained in the label, and embedding positioning points in the original invisible image coded image;
step 2: printing an invisible graphic coding image containing a positioning point on a label printing medium;
and step 3: shooting a printed coded image;
and 4, step 4: carrying out binarization and black-and-white morphological processing on the shot image;
and 5: identifying the embedded positioning points from the image processed in the step 4 according to the difference of the areas of the data points and the positioning point communication components, and calculating corresponding positioning point coordinates by using a centroid method;
step 6: and determining the corresponding relation of the positioning points according to a triangular positioning identification principle, positioning the image, and performing geometric transformation on the image so as to realize image matching.
In step 1, the original invisible image coded image is a color image including invisible data points and positioning points, the points serving as effective data are 2 × 2 pixels, the points serving as positioning are 3 × 3 pixels, and the area ratio of the data points to the positioning points is 4: 9.
in step 4, the binary result is processed by black and white morphology, and the area S of each connected component is calculated i ：
S i ＝num
And num is the number of pixel points in a certain connected region.
In step 5, according to the result of the black-and-white morphological processing, the three connected regions with the largest area are reserved, the row-column coordinates (r, c) of the centroids of the three connected regions with the largest area are calculated,
wherein r is i ,c i Respectively is the row-column coordinate of each point in the connected component, and k is the number of points in the connected component.
In step 6, the image matching method based on the triangulation location identification principle is as follows:
in the original image, black points p1, p2, p3 represent anchor points, the anchor points are identified, and are determined by applying an isosceles right triangle, wherein | p1p2| ═ p1p3|, < p2p1p3 ═ 90 °, the fourth point p4 is a symmetric point of p1 about the line segment p2p3, and four points are on four vertexes of a square as index points in the original image;
three anchor points are identified from the image as q1, q2 and q3, and their coordinate points are (x) 1 ,y 1 )，(x 2 ,y 2 )，(x 3 ,y 3 ) The matching of the positioning points is carried out according to the following principle:
(1) calculating the distance between two points A (x) on the plane 1 ,y 1 ),B(x 2 ,y 2 ) The distance between two points is expressed as:
the largest distance is the oblique side, the two corresponding points are marked as q2 and q3, the other point is q1, and q1 corresponds to p 1;
(2) compute vector q1q 2: ((x) 2 -x 1 )，(y 2 -y 1 ) 0) and q1q3: ((x) 3 -x 1 )，(y 3 -y 1 ) 0) a vector product; the vector product of the two vectors a and b is written as a multiplied by b, the result of the vector product is a vector, the direction of the vector is perpendicular to the plane of the two vectors a and b, and the right-hand rule is observed;
q1q2×q1q3＝(0,0,(x 2 -x 1 )(y 3 -y 1 )-(x 3 -x 1 )(y 2 -y 1 ))
if (x) 2 -x 1 )(y 3 -y 1 )-(x 3 -x 1 )(y 2 -y 1 ) The sign of the result is positive, q2 is matched with p3, q3 is matched with p2, otherwise q2 and q3 are respectively matched with p2 and p 3;
(3) according to the coordinate values of q1, q2 and q3, the coordinates of a symmetric point q4 of the q1 relative to the line segment q2q3 are calculated as follows:
x 4 ＝x 2 +x 3 -x 1 ,y 4 ＝y 2 +y 3 -y 1
points q1, q2, q3, q4 match p1, p2, p3, p4, respectively;
(4) and constructing projection transformation according to the coordinates of the four pairs of matching points, calibrating the image, and matching the calibrated image with the standard image so as to complete the task of image positioning.
Step 6, rotating the invisible image coded image T0 containing the positioning points by 90, 180 and 270 degrees in a counterclockwise manner to respectively obtain three images T1, T2 and T3, and splicing to form a graph formed by a plurality of groups of data; finding each group of positioning points, determining a projective transformation for each group of positioning points, obtaining four projective transformations, and obtaining a group of data identification results for the results of each projective transformation, so that at least four groups of results are mutually verified.
The invention has the following beneficial effects:
(1) the positioning point identification method in the anti-counterfeiting invisible graph code of the commodity label is simple in principle, small in calculated amount, rapid and accurate;
(2) the deformation robustness to the commodity label is good, and the anti-interference capability is strong;
(3) in the printing of the commodity label, the label is invisible to naked eyes, and the character coding rule is self-defined, so that the invisible and anti-counterfeiting capabilities are strong.
Drawings
FIG. 1 is a flow chart of the operation of the present invention;
FIG. 2 is an image containing anchor points and valid data;
FIG. 3 shows the result of image binarization;
FIG. 4 is a diagram of anchor point locations;
FIG. 5 is a photograph of a mobile phone;
FIG. 6 is a diagram of a multi-group image stitching method;
FIG. 7 is an image containing multiple sets of location points and data points;
FIG. 8 is a photograph of a mobile phone;
FIG. 9 is a diagram of binarization results;
fig. 10 is a diagram of positioning results.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
The technical flow chart of the invention is as shown in figure 1, firstly, the original information is subjected to graphic coding, the coded data points are 2 x 2 pixel points, and random noise points as large as the data points are added into the original information image to obtain an original invisible graphic coded image. And embedding positioning points in the original invisible image coded image, wherein the positioning points are 3 x 3 pixels. An image containing data points, noise points and anchor points is printed on a printing medium by using a printer or a printing machine and the like. And then image acquisition is carried out by using image acquisition equipment such as a mobile phone and the like, and the image is transmitted to a computer for processing. Image preprocessing work such as binarization, morphological processing and the like is carried out on the collected image so as to eliminate the influence of illumination, distortion, inclination and the like. Identifying embedded positioning points in the preprocessed image according to different areas of the data points and the positioning point communication components, and calculating corresponding positioning point coordinates by using a centroid method; and finally, determining the corresponding relation of the positioning points according to a triangular positioning identification principle, positioning the image, and performing geometric transformation on the image so as to realize image matching.
Embedding of anchor points
In the original color image containing data points, most of the area is an effective data area, the data area contains data points, the points serving as effective data are 2 x 2 pixels, and meanwhile, a plurality of random noise points with the same size are added. Embedding positioning points in the original image, wherein the points serving as positioning are 3 pixels by 3 pixels, and the area ratio of the data points to the positioning points is 4: 9. as shown in fig. 2, is an image containing a set of anchor points.
Image binarization
And preprocessing the acquired image to eliminate the influence caused by uneven illumination. The binarization result of the original image shown in fig. 2 is shown in fig. 3, wherein the black point is the data point and the white point is the background.
Morphological treatment
The binary result is processed morphologically to eliminate the interference caused by random noise, etc., the effective locating point information is maintained, and the area S of each connected component is calculated i ：
S i ＝num
And num is the number of pixel points in a certain connected region.
Identification of anchor points
According to the result of the morphological processing, the three connected regions with the largest area are reserved, the centroid coordinates of the three connected regions with the largest area are calculated, the centroid is the corresponding geometric center, and the coordinate value of the geometric center point is obtained. Finite set of points x for a connected region i (r i ,c i )∈R 2 K, whose centroid coordinate formula center defines C as:
wherein r is i ,c i Respectively are the row-column coordinates of each point in the connected region, and k is the number of points in the connected region.
Principle of triangulation
In image calibration, at least one set of four pairs of points is needed to be able to realize the calibration of the image by using the projective transformation. The present study designs a positioning scheme based on triangulation, and the principle is as follows.
As shown in fig. 4, in the original image, black points P1, P2, and P3 represent anchor points, which are marked and are designed by applying an isosceles right triangle, where | P1P2| ═ P1P3|, and ═ P2P1P3 ═ 90 °, then the fourth point P4 is a symmetric point of P1 with respect to the line segment P2P3, and four points are at four vertices of a square as index points in the original image. During the image scanning process, the positions of the points and the proportion of the side length are changed, as shown in fig. 5, so that if the correction is needed, the positions of the positioning points need to be found.
When we identify three fixes from the imageThe positions are respectively marked as q1, q2 and q3, and the coordinate points are respectively (x) 1 ,y 1 )，(x 2 ,y 2 )，(x 3 ,y 3 ) The matching of the positioning points is carried out according to the following principle:
(1) calculating the distance between two points A (x) on the plane 1 ,y 1 ),B(x 2 ,y 2 ) The distance between two points is expressed as:
the largest distance is the oblique side, the two corresponding points are marked as q2 and q3, the other point is q1, and q1 corresponds to p 1;
(2) compute vector q1q 2: ((x) 2 -x 1 )，(y 2 -y 1 ) 0) and q1q3: ((x) 3 -x 1 )，(y 3 -y 1 ) 0) a vector product; the vector product of the two vectors a and b is written as a multiplied by b, the result of the vector product is a vector, the direction of the vector is perpendicular to the plane of the two vectors a and b, and the right-hand rule is observed; q1q2 × q1q3 ═ 0,0, (x) 2 -x 1 )(y 3 -y 1 )-(x 3 -x 1 )(y 2 -y 1 ))
If the sign of the result of q1q2 xq 1q3 is positive, q2 is matched with p3, and q3 is matched with p2, otherwise, q2 and q3 are respectively matched with p2 and p 3;
(3) according to the coordinate values of q1, q2 and q3, the coordinates of a symmetric point q4 of the q1 relative to the line segment q2q3 are calculated as follows:
x 4 ＝x 2 +x 3 -x 1 ,y 4 ＝y 2 +y 3 -y 1
the points q1, q2, q3 and q4 are respectively matched with p1, p2, p3 and p 4;
(4) and constructing projection transformation according to the coordinates of the four pairs of matching points, calibrating the image, and matching the calibrated image with the standard image so as to complete the task of image positioning.
Principle of positioning multiple groups of images
An image T0 as shown in fig. 2 is rotated by 90, 180, and 270 degrees counterclockwise to obtain three images T1, T2, and T3, which are spliced in the manner of fig. 6 to form fig. 7 composed of multiple sets of data.
Fig. 6 shows a manner of stitching the images T0, T1, T2, and T3. Fig. 7 is a plurality of images containing data points and positioning points obtained by splicing the original images in fig. 2 according to the splicing method of fig. 6.
According to the locating point identification principle, each group of locating points is found, each group of locating points can determine a projection transformation, so that four groups of locating points can obtain four projection transformations, and the result of each projection transformation can obtain a group of data identification results, so that at least four groups of results are mutually verified.
In this embodiment, the original image is set to 300 × 300 pixels, anchor points are embedded at three points (22,22), (22,278), (278,22), and graphics-encoded data is added to the anchor points, and the anchor points are combined according to a combination scheme of multiple sets of images to form an image of 600 × 600 pixels, and then the image is rotated and translated by using the aforementioned multiple-set image combination principle, and finally combined into a multiple-set image with rotation invariance. Fig. 8 shows the images taken by the mobile phone, and the result of the image taken is 800 × 600. The distances between the positioning points and the boundary in the figure are different, and the positioning points have certain distortion and rotation deformation. The result of the processing by the 2.4 image binarization method is shown in fig. 9.
For fig. 9, four sets of coordinates of the positioning points are obtained by the aforementioned positioning method:
a first group: (553.0000165.0000),(560.0000384.0000),(333.0000171.5000)
Second group: (568.0000624.0000),(560.6364403.9091),(348.0000630.7143)
Third group: (94.0000179.0000),(313.1250172.1250),(101.1250398.1250)
And a fourth group: (108.0000638.0000),(328.0000631.7143),(101.8750418.1250)
After the positioning, the photographed image is transformed back to the positioned image by inverse transformation, as shown in fig. 10, and then matched with the standard image.
The invention is established on the premise of an invisible graphic code, and the invisible graphic code has the characteristics of simple background, noise point inclusion, translation, rotation invariance and the like; the decoding algorithm has strong fault-tolerant capability, small calculated amount, rapidness and accuracy.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A method for identifying a locating point in an invisible graph code on a commodity label is characterized by comprising the following steps:
step 1: carrying out invisible graphic coding on the label contained information, and embedding positioning points in the original invisible graphic coded image;
step 2: printing an invisible graphic coding image containing a positioning point on a label printing medium;
and step 3: shooting a printed coded image;
and 4, step 4: carrying out binarization and black-and-white morphological processing on the shot image;
and 5: identifying the embedded positioning points from the image processed in the step 4 according to the difference of the areas of the data points and the positioning point communication components, and calculating corresponding positioning point coordinates by using a centroid method;
step 6: and determining the corresponding relation of the positioning points according to a triangular positioning identification principle, positioning the image, and performing geometric transformation on the image so as to realize image matching.
2. The method for identifying the positioning point in the invisible pattern code on the commodity label according to claim 1, wherein in the step 1, the original invisible pattern code image is a color image containing invisible data points and positioning points, the points serving as effective data are 2 x 2 pixels, the points serving as positioning are 3 x 3 pixels, and the area ratio of the data points to the positioning points is 4: 9.
3. the method as claimed in claim 1, wherein in step 4, the binarization result is processed by black and white morphology, and the area S of each connected component is calculated i 。
4. The method as claimed in claim 1, wherein in step 5, the three connected regions with the largest area are retained according to the result of the black-white morphological processing, and the coordinates (r, c) of the row and column where the centroid of the three connected regions with the largest area is located are calculated,
wherein r is i ,c i Respectively is the row-column coordinate of each point in the connected component, and k is the number of points in the connected component.
5. The method for identifying a locating point in an invisible pattern code on a commodity label according to claim 1, wherein in step 6, the image matching method based on the triangulation identification principle comprises the following steps:
in the original image, black points p1, p2, p3 represent anchor points, the anchor points are identified, and are determined by applying an isosceles right triangle, wherein | p1p2| ═ p1p3|, < p2p1p3 ═ 90 °, the fourth point p4 is a symmetric point of p1 about the line segment p2p3, and four points are on four vertexes of a square as index points in the original image;
three anchor points are identified from the acquired image as q1, q2 and q3 respectively, and the coordinate points are (x) 1 ,y 1 )，(x 2 ,y 2 )，(x 3 ,y 3 ) The matching of the positioning points is carried out according to the following principle:
(1) calculating the distance between two points A (x) on the plane 1 ,y 1 ),B(x 2 ,y 2 ) The distance between two points is expressed as:
the largest distance is the oblique side, the two corresponding points are marked as q2 and q3, the other point is q1, and q1 corresponds to p 1;
(2) and (3) calculating a vector:
q1q2:((x 2 -x 1 ),(y 2 -y 1 ) 0) and q1q3: ((x) 3 -x 1 ),(y 3 -y 1 ) 0) a vector product; the vector product of the two vectors a and b is written as a multiplied by b, the result of the vector product is a vector, the direction of the vector is perpendicular to the plane of the two vectors a and b, and the right-hand rule is observed;
q1q2×q1q3＝(0，0，(x 2 -x 1 )(y 3 -y 1 )-(x 3 -x 1 )(y 2 -y 1 ))
if (x) 2 -x 1 )(y 3 -y 1 )-(x 3 -x 1 )(y 2 -y 1 ) The sign of the result is positive, q2 is matched with p3, q3 is matched with p2, otherwise q2 and q3 are respectively matched with p2 and p 3;
(3) according to the coordinate values of q1, q2 and q3, the coordinates of a symmetric point q4 of the q1 relative to the line segment q2q3 are calculated as follows:
x 4 ＝x 2 +x 3 -x 1 ,y 4 ＝y 2 +y 3 -y 1
the points q1, q2, q3 and q4 are respectively matched with p1, p2, p3 and p 4;
(4) and constructing projection transformation according to the coordinates of the four pairs of matching points, calibrating the image, and matching the calibrated image with the standard image so as to complete the task of image positioning.
6. The method for identifying the positioning points in the invisible pattern codes on the commodity labels according to claim 1, wherein in the step 6, the invisible pattern code images T0 containing the positioning points rotate by 90, 180 and 270 degrees counterclockwise to respectively obtain three images T1, T2 and T3, and the three images are spliced to form a graph formed by multiple groups of data; finding each group of positioning points, determining a projective transformation for each group of positioning points, obtaining four projective transformations, and obtaining a group of data identification results for the results of each projective transformation, so that at least four groups of results are mutually verified.
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