CN112926350A - Method and terminal for identifying two-dimensional codes in batches - Google Patents
Method and terminal for identifying two-dimensional codes in batches Download PDFInfo
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- 238000004590 computer program Methods 0.000 claims description 10
- 238000002372 labelling Methods 0.000 claims description 6
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- 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
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
- G06K7/1417—2D bar codes
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- 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
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- 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
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- 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
- G06K7/1452—Methods for optical code recognition including a method step for retrieval of the optical code detecting bar code edges
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Abstract
The invention discloses a method and a terminal for identifying two-dimension codes in batches, wherein the method comprises the following steps: obtaining a gray image of the two-dimensional code to be identified; reducing the obtained gray level image by one time in the width direction and the height direction; carrying out averaging processing on the reduced image to remove noise; carrying out binarization processing on the image subjected to the averaging processing; finding out all connected regions of the image after binarization processing, and removing noise points; obtaining all rectangular connected regions in the image; judging whether a rectangular communication area has more than four pixel cells; and judging whether the rectangular connected regions under different image proportions have overlapped regions or not to obtain all non-overlapped rectangular connected regions. The invention can realize batch identification of the two-dimensional codes and has high identification precision.
Description
Technical Field
The invention relates to the field of image identification processing, in particular to a method and a terminal for identifying two-dimensional codes in batches.
Background
At present, two-dimensional codes such as QR (Quick Response Code) codes are widely applied to different scenes of various industries, and almost relate to the aspects of life, for example, mobile payment and information identification are performed through the two-dimensional codes, so that the convenience of daily life is greatly improved. However, the existing two-dimensional code recognition technology recognizes the image characteristics of a specific two-dimensional code, and if there are multiple two-dimensional codes in an image, all the two-dimensional codes need to be recognized, so that not only is the amount of computation greatly increased, but also the existence of two-dimensional codes which are not in a traversal list cannot be judged.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method and a terminal for batch identification of two-dimensional codes, which can realize batch identification of two-dimensional codes and have high identification accuracy.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method for identifying two-dimension codes in batches comprises the following steps:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray scale image by one time in the width direction and the height direction;
SO3, averaging the reduced image to remove noise;
SO4, carrying out binarization processing on the image after the equalization processing;
SO5, finding out all connected regions of the image after binarization processing and removing noise;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions.
Optionally, the obtaining a grayscale image of the two-dimensional code to be identified includes:
reading red, green and blue three-color components of a two-dimensional code color image to be identified;
calculating the gray value of the pixel point;
reassigning the color components of the pixel points;
and obtaining a gray image of the two-dimensional code to be identified.
Optionally, the finding out all connected regions of the binarized image includes:
and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
Optionally, the obtaining all rectangular connected regions in the image includes:
and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four points closest to the middle points of the four edges on the outer boundary of the connected region, and obtaining all rectangular connected regions in the image according to the distances from the four points to the top points.
Optionally, obtaining all rectangular connected regions in the image according to the distances from the four points to the vertex includes: and if the distances from the four points to the vertex are 0, judging that the connected region in the image is a rectangular connected region, and after the connected region is judged to be the rectangular connected region, if the ratio of the long sides to the short sides of the four sides surrounded by the vertex exceeds 3, judging that the connected region is an elongated rectangular connected region, and excluding the elongated rectangular connected region.
A terminal for batch identification of two-dimensional codes, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the following steps:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray scale image by one time in the width direction and the height direction;
SO3, averaging the reduced image to remove noise;
SO4, carrying out binarization processing on the image after the equalization processing;
SO5, finding out all connected regions of the image after binarization processing and removing noise;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions.
Optionally, the obtaining a grayscale image of the two-dimensional code to be identified includes:
reading red, green and blue three-color components of a two-dimensional code color image to be identified;
calculating the gray value of the pixel point;
reassigning the color components of the pixel points;
and obtaining a gray image of the two-dimensional code to be identified.
Optionally, the finding out all connected regions of the binarized image includes:
and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
Optionally, the obtaining all rectangular connected regions in the image includes:
and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four points closest to the middle points of the four edges on the outer boundary of the connected region, and obtaining all rectangular connected regions in the image according to the distances from the four points to the top points.
Optionally, obtaining all rectangular connected regions in the image according to the distances from the four points to the vertex includes: and if the distances from the four points to the vertex are 0, judging that the connected region in the image is a rectangular connected region, and after the connected region is judged to be the rectangular connected region, if the ratio of the long sides to the short sides of the four sides surrounded by the vertex exceeds 3, judging that the connected region is an elongated rectangular connected region, and excluding the elongated rectangular connected region.
Compared with the prior art, the invention has the technical progress that:
according to the invention, the gray level image is reduced by one time in the width direction and the height direction, then after binarization processing, all connected regions are found out through a boundary search algorithm, and the reduced gray level image can quickly identify the rectangular connected regions through the search algorithm.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
fig. 1 is a flowchart illustrating steps of a method for batch identification of two-dimensional codes according to the present invention.
Fig. 2 is a schematic diagram showing that the gray scale image is reduced by one time in both the width direction and the height direction.
FIG. 3 is a schematic diagram of the reduced image equalization process according to the present invention.
FIG. 4 is a schematic diagram of the binarization processing of the image according to the present invention.
FIG. 5 is a schematic diagram of the present invention using a search algorithm to find all connected regions.
Fig. 6 shows the result of the last recognition of the present invention.
Fig. 7 is a block diagram of a terminal for batch identification of two-dimensional codes according to the present invention.
In the figure:
1-memory, 2-processor.
Detailed Description
The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
As shown in fig. 1, the invention discloses a method for identifying two-dimensional codes in batches, which comprises the following steps:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray image by one time in the width direction and the height direction, as shown in FIG. 2;
SO3, averaging the reduced image to remove noise, as shown in FIG. 3;
SO4, carrying out binarization processing on the image after the equalization processing, as shown in figure 4;
SO5, finding out all connected regions of the image after binarization processing, and removing noise points, as shown in FIG. 5;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions, as shown in FIG. 6.
The acquiring of the gray image of the two-dimensional code to be identified in the SO1 includes: and reading red, green and blue three-color components of the two-dimensional code color image to be identified, then calculating the gray value of the pixel point, re-assigning the color component of the pixel point, and finally obtaining the gray image of the two-dimensional code to be identified.
Wherein, finding out all connected regions of the binarized image in SO5 includes: and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
Wherein, obtaining all rectangular connected regions in the image in S06 includes: and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four boundary points closest to the middle points of the four edges on the outer boundary of the connected region, and obtaining all rectangular connected regions in the image according to the distances from the four boundary points to the middle points. Since the common two-dimensional code is rectangular and the black and white cells are uniformly distributed, a rectangular connected region is formed on the image, and each rectangular connected region represents a two-dimensional code.
Obtaining all rectangular connected regions in the image according to the distances from the four boundary points to the middle point comprises: and if the distances from the four boundary points to the middle point are 0, judging that the connected region in the image is a rectangular connected region, and if the ratio of the long side to the short side of the four sides surrounded by the vertexes exceeds 3 after the connected region is judged to be the long and narrow rectangular connected region, excluding the long and narrow rectangular connected region.
Meanwhile, the following method is adopted for eliminating the circular communication area and the annular communication area in the invention:
the method for determining the circular connected region comprises the following steps: and if the ratio of the distance from the boundary point closest to the middle point of one edge to the side length of the edge exceeds one fifth, judging the connected region to be a circular connected region.
The method for determining the annular communication area comprises the following steps: and judging that the communication area is an annular communication area if the area enclosed by the inner edge exceeds one fourth of the area enclosed by the outer edge.
In an actually photographed image, there is a possibility that one black and white cell pixel exceeds four pixels or more, and since there is a 4-domain pixel adjacency relationship, one black and white cell pixel exceeds four pixels to form discrete dots on the image, and therefore, it is necessary to reduce the width and height of the grayscale image by half again, and therefore, it is necessary to repeat steps S02 to S05, and it is generally necessary to identify all two-dimensional codes on the image by reducing the original image twice.
Because at different scales, one rectangular connected region will appear within another rectangular connected region, and thus overlap will be formed.
Example two:
the invention also provides a batch two-dimensional code identification terminal, which comprises a memory 11, a processor 2 and a computer program which is stored on the memory 11 and can be run on the processor 2, wherein the processor 2 realizes the following steps when executing the computer program:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray scale image by one time in the width direction and the height direction;
SO3, averaging the reduced image to remove noise;
SO4, carrying out binarization processing on the image after the equalization processing;
SO5, finding out all connected regions of the image after binarization processing and removing noise;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions.
In the present embodiment, the processor 2 further implements the following steps when executing the computer program: the method for obtaining the gray image of the two-dimensional code to be identified comprises the following steps:
reading red, green and blue three-color components of a two-dimensional code color image to be identified;
calculating the gray value of the pixel point;
reassigning the color components of the pixel points;
and obtaining a gray image of the two-dimensional code to be identified.
In the present embodiment, the processor 2 further implements the following steps when executing the computer program:
finding out all connected regions of the image after the binarization processing comprises the following steps:
and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
In the present embodiment, the processor 2 further implements the following steps when executing the computer program:
obtaining all rectangular connected regions in the image includes:
and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four points closest to the middle points of the four edges on the outer boundary of the connected region, and obtaining all rectangular connected regions in the image according to the distances from the four points to the top points.
In the present embodiment, the processor 2 further implements the following steps when executing the computer program:
obtaining all rectangular connected regions in the image according to the distances from the four points to the vertexes comprises: and if the distances from the four points to the vertexes are 0, judging that the connected region in the image is a rectangular connected region, and if the ratio of the long side to the short side of the four sides surrounded by the vertexes exceeds 3 after the connected region is judged to be the rectangular connected region, judging that the connected region is the long and narrow rectangular connected region, and excluding the long and narrow rectangular connected region.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method for identifying two-dimensional codes in batches is characterized by comprising the following steps:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray scale image by one time in the width direction and the height direction;
SO3, averaging the reduced image to remove noise;
SO4, carrying out binarization processing on the image after the equalization processing;
SO5, finding out all connected regions of the image after binarization processing and removing noise;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions.
2. The method for batch identification of two-dimensional codes according to claim 1, wherein: the obtaining of the gray image of the two-dimensional code to be identified comprises:
reading red, green and blue three-color components of a two-dimensional code color image to be identified;
calculating the gray value of the pixel point;
reassigning the color components of the pixel points;
and obtaining a gray image of the two-dimensional code to be identified.
3. The method for batch identification of two-dimensional codes according to claim 1, wherein: the step of finding out all connected regions of the image after binarization processing comprises the following steps:
and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
4. The method for batch identification of two-dimensional codes according to claim 1, wherein: the obtaining of all rectangular connected regions in the image comprises:
and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four boundary points closest to the middle point of each edge on the outer boundary of each connected region, and obtaining all rectangular connected regions in the image according to the distances from the four boundary points to the middle point.
5. The method for batch identification of two-dimensional codes according to claim 4, wherein: the obtaining of all rectangular connected regions in the image through the distances from the four boundary points to the midpoint includes: and if the distances from the four boundary points to the middle point are 0, judging that the connected region in the image is a rectangular connected region, and if the ratio of the long sides to the short sides of the four sides surrounded by the vertexes exceeds 3 after the connected region is judged to be the rectangular connected region, judging that the connected region is the long and narrow rectangular connected region, and excluding the long and narrow rectangular connected region.
6. The utility model provides a terminal of batch discernment two-dimensional code which characterized in that: comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
SO1, obtaining a gray image of the two-dimensional code to be identified;
SO2, reducing the obtained gray scale image by one time in the width direction and the height direction;
SO3, averaging the reduced image to remove noise;
SO4, carrying out binarization processing on the image after the equalization processing;
SO5, finding out all connected regions of the image after binarization processing and removing noise;
SO6, obtaining all rectangular connected regions in the image;
SO7, judging whether the rectangular communication area has more than four pixel cells, if yes, returning to execute S02 to S06;
and SO8, judging whether the rectangular connected regions under different image proportions have overlapping regions, and obtaining all non-overlapping rectangular connected regions.
7. The terminal for batch identification of two-dimensional codes according to claim 6, wherein: the obtaining of the gray image of the two-dimensional code to be identified comprises:
reading red, green and blue three-color components of a two-dimensional code color image to be identified;
calculating the gray value of the pixel point;
reassigning the color components of the pixel points;
and obtaining a gray image of the two-dimensional code to be identified.
8. The terminal for batch identification of two-dimensional codes according to claim 6, wherein: the step of finding out all connected regions of the image after binarization processing comprises the following steps:
and finding all outer contours of the image after binarization processing and inner contours corresponding to the outer contours by using an OpenCV marking algorithm, and labeling points on the contours to obtain all connected regions.
9. The terminal for batch identification of two-dimensional codes according to claim 6, wherein: the obtaining of all rectangular connected regions in the image comprises:
and finding out four top points of the top, the bottom, the left and the right of the outer boundary of each connected region, connecting every two top points to obtain four edges, finding out four points closest to the middle points of the four edges on the outer boundary of the connected region, and obtaining all rectangular connected regions in the image according to the distances from the four points to the top points.
10. The terminal for batch identification of two-dimensional codes according to claim 9, wherein: the obtaining of all rectangular connected regions in the image through the distances from the four points to the vertex includes: and if the distances from the four points to the vertex are 0, judging that the connected region in the image is a rectangular connected region, and after the connected region is judged to be the rectangular connected region, if the ratio of the long sides to the short sides of the four sides surrounded by the vertex exceeds 3, judging that the connected region is an elongated rectangular connected region, and excluding the elongated rectangular connected region.
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