JP2018036737A - Image processing device for reading multiple bar code - Google Patents

Abstract

PROBLEM TO BE SOLVED: To extract and read a plurality of bar codes from one sheet of an image.SOLUTION: A first module extracts a plurality of first processing blocks from a first image. Each of the plurality of first processing blocks includes a plurality of pixels. A second module calculates an average value of the value showing a gradation of the plurality of pixels with respect to each of the plurality of first processing blocks. A third module calculates a corrected average value by correcting a second average value calculated by the second module with respect to the first processing block on the basis of a plurality of first average values calculated respectively by the second module with respect to a plurality of peripheral blocks located in the periphery of the block. A fourth module generates a second image on the basis of the value showing each gray scale of the plurality of pixels included in the first image and the corrected average value calculated with respect to one block including the pixel from among the plurality of first processing blocks.SELECTED DRAWING: Figure 3

Description

  The present disclosure relates to an image processing apparatus for reading these barcodes from an image including a plurality of barcodes.

  Attempts have been made to read the plurality of barcodes from a single image obtained by photographing a plurality of barcodes together (for example, paragraph 0024 of Patent Document 4 and paragraph 0061 of Patent Document 5). If it is specified which part of an image and which part contains the barcode, a plurality of barcodes can be read by cutting out the designated part from the image. However, when there is no such designation, it is required to determine which part of an image and which part should be cut out.

JP 2011-170882 A JP 2002-150213 A JP 2006-059073 A JP 2013-101481 A JP 2009-266190 A Japanese Patent Application Laid-Open No. 07-028924 JP 09-319821 A

  An image processing apparatus according to an aspect of the present disclosure includes first to fourth modules. The first module extracts a plurality of first processing blocks from the first image, and each of the plurality of first processing blocks includes a plurality of pixels. The second module calculates an average value of the values indicating the gradations of the plurality of pixels for each of the plurality of first processing blocks. For each of the plurality of first processing blocks, the third module is based on the plurality of first average values respectively calculated by the second module for the plurality of peripheral blocks located around the block. A corrected average value is calculated by correcting the second average value calculated by the second module for the block. The fourth module includes a value indicating the gradation of each of the plurality of pixels included in the first image, and one of the plurality of first processing blocks, the one including the pixel A second image is generated based on the corrected average value calculated for the block.

3 is a functional block diagram of an image processing device 40 according to an embodiment of the present disclosure. FIG. The example of the image image | photographed and processed by the said image processing apparatus 40 is shown. 4 is a flowchart showing a process of generating a second image from a first image in the image processing apparatus 40. A part of the first image is shown. A plurality of first processing blocks extracted from the first image in S1000 of FIG. 3 are shown. The example of the average value calculated in S2000 of FIG. 3 is shown. The example of the average value by which the brightness was reduced in S3000 of FIG. 3 is shown. The correction average value calculated in S4000 of FIG. 3 and the correction average value calculation method are shown. The part corresponding to FIG. 8 is shown among the 2nd images produced | generated in S5000 of FIG. The part corresponding to FIG. 4 is shown among the 2nd images produced | generated in S5000 of FIG. 4 is a flowchart showing details of a process of analyzing a one-dimensional barcode in the image processing apparatus 40. A plurality of second processing blocks extracted from the second image in S6100 of FIG. 11 are shown. 4 is a flowchart showing details of processing for extracting a second processing block in the image processing apparatus 40; A process of determining whether or not the block is a valid block is shown. It is a flowchart which shows the detail of the process which determines whether the said block is an effective block in the said image processing apparatus. 4 is a flowchart showing details of processing for determining a one-dimensional barcode area in the image processing apparatus 40; 4 is a flowchart showing details of processing for extracting an n-th one-dimensional barcode area in the image processing apparatus 40. The state which linked | related the effective block which adjoins or partially overlaps is shown. The state where the one-dimensional barcode area is enlarged is shown. 4 is a flowchart showing details of a process of analyzing a two-dimensional barcode in the image processing apparatus 40. A plurality of second processing blocks extracted from the second image in S6500 of FIG. 20 are shown. The determination result of whether it is an effective block about each of several 2nd processing blocks is shown. 4 is a flowchart showing details of processing for determining a two-dimensional barcode area in the image processing apparatus 40; 5 is a flowchart showing details of processing for extracting an n-th two-dimensional barcode area in the image processing apparatus 40. The process of extracting a two-dimensional barcode area is shown. 4 is a flowchart showing details of a process of reading a two-dimensional barcode in the image processing apparatus 40. An example of the range of an image cut out in S6901 and an example of an image processing variation are shown.

  Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Each embodiment described below shows an example of this indication, and does not limit the contents of this indication. In addition, not all of the configurations and operations described in the embodiments are essential as the configurations and operations of the present disclosure. In addition, the same referential mark is attached | subjected to the same component and the overlapping description is abbreviate | omitted.

  In the present disclosure, “one-dimensional barcode” refers to a barcode in which monochrome patterns are arranged in one direction. “Two-dimensional barcode” refers to a barcode in which black and white patterns are arranged in two directions intersecting each other. “White” and “black” do not mean white and black in a strict sense, “white” means a lighter color than a certain lightness, and “black” is a darker color than the above certain lightness. It shall be said.

<1. Configuration of Image Processing Device>
FIG. 1 is a functional block diagram of an image processing device 40 according to an embodiment of the present disclosure. The image processing device 40 includes an input / output unit 10, an imaging unit 20, and a processing unit 30.

  The input / output unit 10 includes a device that can input and output information, such as a touch panel. Alternatively, the input / output unit 10 may include an input device and an output device separately. The input / output unit 10 can receive input of setting information, imaging instructions, and the like by the user and can transmit the input to the processing unit 30. The input / output unit 10 can display an image processed by the processing unit 30, a barcode decoding result by the processing unit 30, and the like.

  The imaging unit 20 includes a CCD camera. The imaging unit 20 can take an image in accordance with a drive signal from the processing unit 30 and transmit image data to the processing unit 30.

  The processing unit 30 includes a processor, a main storage device, a storage memory, and the like. The storage memory stores an image processing program 31 and a barcode analysis program 32 that can be executed by the processor. The barcode analysis program 32 may be stored in a device different from the image processing device 40 shown in FIG. The calculation result by the image processing program 31 may be transmitted to the other device, and the barcode decoding result using the barcode analysis program may be received from the other device. The processing unit 30 exchanges the above data or signals with the input / output unit 10 and with the imaging unit 20.

  The image processing apparatus 40 having the various functions described above can be configured by, for example, one mobile phone.

<2. Example of use of image processing device>
FIG. 2 shows an example of an image taken and processed by the image processing device 40. For example, the image processing apparatus 40 captures a plurality of products 51 placed on the tray 50 and acquires one image. Various characters 52 and barcodes 53 are printed on the plurality of products 51. The designs of the plurality of products 51 are various, and the printing location and size of the barcode 53 may be various. By reading the bar codes 53 of such various products 51 from one image, for example, it is possible to manage how many products are shipped. In addition, a wide range of applications are possible, such as warehouse management in the distribution industry and drug management in the medical industry.

<3. Processing for generating second image from first image>
FIG. 3 is a flowchart showing a process of generating a second image from the first image in the image processing apparatus 40. The processing unit 30 of the image processing apparatus 40 executes the image processing program 31 and generates a second image from the first image by the following processing. The first image is an original image captured by the imaging unit 20, for example. The second image is, for example, a binary image in which the monochrome pattern portion is emphasized so that the barcode area can be easily extracted in later processing. In the present disclosure, the process of generating the second image from the first image is common to the reading of the one-dimensional barcode and the reading of the two-dimensional barcode, but each is separate within the scope of the present disclosure. May be modified.

  FIG. 4 shows a part of the first image. FIG. 4 shows a portion of the first image that includes one one-dimensional barcode and a part of another one-dimensional barcode. Although FIG. 4 shows a gray scale image for the convenience of the patent application format, the first image may be a color image. The gradation in the photographed image may be affected by photographing conditions such as how light strikes the subject. In addition, as described with reference to FIG. 2, it may be difficult to specify a one-dimensional barcode area when shooting products with various designs. Therefore, a second image in which the monochrome pattern portion is emphasized is generated by the following processing.

  In S1000 of FIG. 3, the processing unit 30 extracts a plurality of first processing blocks from the first image. The first processing block includes a plurality of pixels. The module that performs the process of S1000 may correspond to the first module of the present disclosure.

  FIG. 5 shows a plurality of first processing blocks extracted from the first image in S1000 of FIG. FIG. 5 shows a portion within the thick frame line of FIG. In order to simplify the description, in FIG. 5, each of the plurality of first processing blocks includes 16 pixels of 4 rows × 4 columns, but may include 64 pixels of 8 rows × 8 columns. Good. Further, FIG. 5 shows an example of numerical values indicating the gradation of each pixel. In addition, each pixel is shown in different colors according to the numerical value indicating the gradation. In FIG. 5, the numerical value indicating the gradation is 16 gradations from 0 to 15 for convenience of the paper width, but may be 256 gradations from 0 to 255. Here, the smaller the numerical value indicating the gradation, the lower the lightness and the darker the color. The higher the numerical value indicating the gradation, the higher the lightness and the brighter the color.

Next, in S2000 of FIG. 3, the processing unit 30 calculates an average value of values indicating gradation for each of the plurality of first processing blocks. In the example shown in FIG. 5 described above, the values indicating the gradations of the 16 pixels included in each of the plurality of first processing blocks are summed, and the total value is divided by the number of pixels of 16.
FIG. 6 shows an example of the average value calculated in S2000 of FIG. One average value is calculated for one first processing block.

  Next, in S3000 of FIG. 3, the processing unit 30 reduces the brightness of the average value of the values indicating the gradation for each of the plurality of first processing blocks. As described above, when the value is lower, the lightness is lower, for example, each of the average values shown in FIG. 6 is multiplied by a reduction rate of less than 1. For example, the reduction rate is set in a range of 0.7 to 0.95. Since the optimum value of the reduction rate may change depending on the brightness of the shooting site, etc., it may be set by the user using the input / output unit 10. Alternatively, in order to reduce the brightness in S3000, a certain offset value may be subtracted from each of the average values shown in FIG. 6 (however, it is not a negative number).

FIG. 7 shows an example of the average value in which the brightness is reduced in S3000 of FIG. In FIG. 7, each of the average values shown in FIG. 6 is multiplied by 0.8.
The module that performs the process of S2000, or the module that performs the processes of S2000 and S3000 may correspond to the second module of the present disclosure. The second module may or may not perform the process of reducing the lightness of the average value. Alternatively, the second module may replace the processing order of S2000 and S3000 to reduce the brightness for each of the plurality of pixels, and then calculate an average value for each of the plurality of first processing blocks. If the processing order of S2000 and S3000 is changed, the amount of calculation increases slightly, but the effect of the present disclosure can still be achieved.

  Next, in S4000 of FIG. 3, the processing unit 30 calculates the corrected average value of each of the plurality of first processing blocks as follows. The module that performs the process of S4000 may correspond to the third module of the present disclosure.

FIG. 8 shows the corrected average value calculated in S4000 of FIG. 3 and a method for calculating the corrected average value. The corrected average value of the block includes a plurality of first average values D1 to D8 calculated for each of a plurality of peripheral blocks located around the block, and a second average value D calculated for the block. Is used to calculate. The first average values D1 to D8 and the second average value D are the average values shown in FIG. 6 or FIG. As shown in the lower part of FIG. 8, among the first average values D1 to D8, D1 to D4 are average values of blocks adjacent to the block in the vertical and horizontal directions, and D5 to D8 are the blocks of the block. It is an average value of blocks at positions shifted in an oblique direction. The corrected average value E is calculated by the following formula.
E = [4 × D + 2 × (D1 + D2 + D3 + D4) + (D5 + D6 + D7 + D8)] / 16
As described above, the second average value D calculated for the block is corrected based on the plurality of first average values D1 to D8 respectively calculated for the plurality of peripheral blocks located around the block. Is done.
The corrected average value E is calculated by giving a first weight 1 or 2 to the first average values D1 to D8, and giving a second weight 4 larger than the first weight to the second average value D. The average value of the first average values D1 to D8 and the second average value D. These weight values may be changed to other values. Furthermore, not only the eight blocks adjacent to each other in the vertical and horizontal directions and diagonally, but also a block located further around the eight blocks may be taken into consideration. In this case, it is desirable to give a greater weight to a block located near the block than a block located far from the block.

  FIG. 8 does not show the calculation result of the correction average value for the processing block in which the correction average value cannot be calculated only by the gradation data of the region shown in FIG. However, the corrected average value may be calculated using peripheral gradation data.

  Next, in S5000 of FIG. 3, the processing unit 30 generates a second image as follows. The module that performs the process of S5000 may correspond to the fourth module of the present disclosure.

  FIG. 9 shows a portion corresponding to FIG. 8 in the second image generated in S5000 of FIG. In S5000, the processing unit 30 compares the value indicating the gradation of each of the plurality of pixels included in the first image with the corrected average value calculated for the first processing block to which the pixel belongs. When the value indicating the gradation of the pixel shown in FIG. 5 is larger than the corrected average value shown in FIG. 8, that is, the lightness is high, the pixel in the second image is set as a white point (0). When the value indicating the gradation of the pixel shown in FIG. 5 is smaller than the corrected average value shown in FIG. 8, that is, when the brightness is low, the pixel in the second image is set as a black point (1). A binary image is generated as described above.

  FIG. 10 shows a portion corresponding to FIG. 4 in the second image generated in S5000 of FIG. As shown in FIG. 10, in the second image, the shade of the background portion of the first image is considerably erased, and the black and white repetitive pattern in the one-dimensional barcode is emphasized. Such a second image can be generated because the value indicating the gradation of the pixel is compared with the surrounding correction average value. Furthermore, in the present embodiment, since the processes of S3000 and S4000 are performed in units of blocks, the amount of calculation is reduced according to the block size. For example, if the block size is 4 rows × 4 columns, the calculation amount of S3000 and S4000 is 1/16. The processing of S5000 requires a calculation amount corresponding to the number of pixels, but the number of readings of the corrected average value is reduced according to the block size.

  Next, in S6000 of FIG. 3, the processing unit 30 analyzes the barcode. By performing the process of S6000 using the second image described above, the barcode area can be specified at high speed and the barcode can be analyzed accurately. Details of the processing of S6000 will be described below by dividing into one-dimensional barcode analysis (FIGS. 11 to 19) and two-dimensional barcode analysis (FIGS. 20 to 27).

<4. Analysis of one-dimensional barcode>
FIG. 11 is a flowchart showing details of processing for analyzing a one-dimensional barcode in the image processing apparatus 40. The processing shown in FIG. 11 is performed by the processing unit 30 as a subroutine of S6000 in FIG. The processing shown in FIG. 11 is performed based on the image processing program 31 unless otherwise specified.

<4-1. Extraction of second processing block>
First, in S6100 of FIG. 11, the processing unit 30 extracts a plurality of second processing blocks from the second image generated in S5000 of FIG. The second processing block includes a plurality of pixels. The second processing block may have the same number of pixels as the first processing block, or may have a different number of pixels. The number of pixels of the second processing block may be set by the user using the input / output unit 10. Further, when the one-dimensional barcode direction is input by the user, the second processing block is set so as to partially overlap in the direction intersecting the one-dimensional barcode direction. Here, the “one-dimensional barcode direction” refers to the repeating direction of the black-and-white repeating pattern included in the one-dimensional barcode. The module that performs the process of S6100 may correspond to the fifth module of the present disclosure.

  FIG. 12 shows a plurality of second processing blocks extracted from the second image in S6100 of FIG. In FIG. 12, each of the plurality of second processing blocks includes 256 pixels of 16 rows × 16 columns. In FIG. 12, the one-dimensional barcode direction is the horizontal direction. In this case, the second processing block is set so as to partially overlap in the vertical direction.

  Here, when the block number (i, j) is specified by using the horizontal coordinate i and the vertical coordinate j, the block number (1, 1) is the second number relative to the block number (1, 1). The processing block is overlapped by half the vertical length. That is, the block number (1, 2) is shifted from the block number (1, 1) by half the vertical length of the second processing block. By setting the second processing block in this way, an appropriate range of one-dimensional barcode area can be extracted even if the width of the one-dimensional barcode in the direction perpendicular to the one-dimensional barcode direction is narrow. . Thereby, the specific precision of a one-dimensional barcode area | region can be improved.

  FIG. 13 is a flowchart showing details of processing for extracting the second processing block in the image processing apparatus 40. The processing shown in FIG. 13 is performed by the processing unit 30 as a subroutine of S6100 in FIG.

  First, in S6101, the processing unit 30 determines whether or not a one-dimensional barcode direction has been input. When the user inputs a one-dimensional barcode direction, it is preferable that the user captures a plurality of one-dimensional barcodes with the one-dimensional barcode direction substantially aligned as shown in FIG.

  When the one-dimensional barcode direction is not input (S6101; NO), the processing unit 30 stands by until the one-dimensional barcode direction is input. Alternatively, the processing unit 30 may set the second processing block so that the second processing block does not overlap. Alternatively, the processing unit 30 may set the second processing block so that the second processing block partially overlaps in both the vertical and horizontal directions.

  When the one-dimensional barcode direction is input (S6101; YES), the processing unit 30 advances the process to S6102. In S6102, the processing unit 30 sets the second processing block so that the second processing block partially overlaps in the direction perpendicular to the one-dimensional barcode direction. After S6102, the processing unit 30 ends the process of this flowchart and returns to the process illustrated in FIG.

<4-2. Determining whether the block is valid>
In S6200 of FIG. 11, the processing unit 30 determines, for each of the plurality of second processing blocks, whether the block is an effective block. The module that performs the process of S6200 may correspond to the sixth module of the present disclosure. The determination as to whether the block is a valid block is performed as follows.
FIG. 14 shows the process of determining whether or not the block is a valid block. FIG. 14 shows block numbers (4, 4) corresponding to the portions within the thick frame in FIG.
FIG. 15 is a flowchart showing details of processing for determining whether or not the block is an effective block in the image processing apparatus 40. The processing shown in FIG. 15 is performed by the processing unit 30 as a subroutine of S6200 in FIG.

First, in S6201 of FIG. 15, the processing unit 30 extracts a plurality of columns in a direction intersecting with the one-dimensional barcode direction, and counts the number of black points and the number of white points in each column. The plurality of columns in a direction that intersects the one-dimensional barcode direction may correspond to the plurality of first columns or rows of the present disclosure.
Near the upper end of FIG. 14, the number of black spots in each column is shown. The number of white spots in each row is shown near the center of FIG. In each column, the total number of black spots and white spots is 16, and this value is equal to the block size Block_size.

In S6202 of FIG. 15, the processing unit 30 extracts a plurality of rows in the one-dimensional barcode direction, and counts the number of black spots and the number of white spots in each row in the one-dimensional barcode direction. The plurality of rows in the one-dimensional barcode direction may correspond to the plurality of second rows or columns of the present disclosure.
Near the left end of FIG. 14, the number of black dots in each row is shown. Near the right end of FIG. 14, the number of white spots in each row is shown. In each row, the total number of black spots and white spots is 16, and this value is equal to the block size Block_size.

  Next, in S6203 of FIG. 15, the processing unit 30 determines whether each line is a black line or a white line. If the number of black dots in each column is greater than the first threshold, it is determined that the column is a black line. The first threshold value is set to a value larger than the average value of the number of black spots in each column, for example, a value that is 1.1 times or more and 1.3 times or less of the average value. If the number of white dots in each column is greater than the second threshold, it is determined that the column is a white line. The second threshold value is set to a value larger than the average value of the number of white spots in each column, for example, a value that is 1.1 times or more and 1.3 times or less of the average value.

In the vicinity of the upper end of FIG. 14, the determination result as to whether or not each column is a black line is shown. The first threshold value is set to a value larger than the average of the number of black spots in each column. The determination result as to whether or not it is a vertical black line is indicated as 1 if it is a vertical black line, and 0 if it is not a vertical black line.
In the vicinity of the center of FIG. 14, the determination result as to whether or not each line is a white line is shown. The second threshold value is set to a value larger than the average of the number of white spots in each column. The determination result as to whether or not it is a vertical white line is indicated as 1 if it is a vertical white line and 0 if it is not a vertical white line.

Next, in S6204 of FIG. 15, the processing unit 30 counts the number of vertical black lines HORZblack and the number of vertical white lines HORZwhite.
Near the upper end of FIG. 14, the calculation result of the number of vertical black lines HORZblack is shown.
The calculation result of the number of vertical white lines HORZwhite is shown near the center of FIG.

  Next, in S6205 of FIG. 15, the processing unit 30 determines whether the sum of the number of vertical black lines HORZblack and the number of vertical white lines HORZwhite is greater than a first predetermined value. The first predetermined value may be a value obtained by multiplying the block size Block_size by a predetermined determination rate. The determination rate has a value of 0.2 or more and 0.3 or less, for example.

When the sum of the number of vertical black lines HORZblack and the number of vertical white lines HORZwhite is not larger than the first predetermined value (S6205; NO), the processing unit 30 advances the processing to S6210.
When the sum of the number of vertical black lines HORZblack and the number of vertical white lines HORZwhite is larger than the first predetermined value (S6205; YES), the processing unit 30 advances the process to S6206.

  In S6206 of FIG. 15, the processing unit 30 determines whether each line is a black line or a white line. If the number of black dots in each row is greater than the first threshold, it is determined that the row is a black line. The first threshold value is set to a value larger than the average of the number of black spots. If the number of white spots in each row is greater than the second threshold, it is determined that the row is a white line. The second threshold value is set to a value larger than the average number of white spots in each row.

Near the left end of FIG. 14, the determination result of whether or not each line is a black line is shown. The first threshold value is set to a value larger than the average of the number of black spots in each row. The determination result as to whether or not it is a horizontal black line is indicated as 1 if it is a horizontal black line and 0 if it is not a horizontal black line.
In the vicinity of the center of FIG. 14, the determination result as to whether or not each line is a white line is shown. The second threshold value is set to a value larger than the average number of white spots in each row. The determination result as to whether or not it is a horizontal white line is indicated as 1 if it is a horizontal white line and 0 if it is not a horizontal white line.

Next, in S6207 of FIG. 15, the processing unit 30 counts the number of horizontal black lines VERTblack and the number of horizontal white lines VERTwhite.
Near the left end of FIG. 14, the calculation result of the number of horizontal black lines VERTblack is shown.
The calculation result of the number of horizontal white lines VERTwhite is shown near the right end of FIG.

Next, in S6208 of FIG. 15, the processing unit 30 compares the difference between the number of vertical black lines HORZblack and the number of horizontal black lines VERTblack, the number of vertical white lines HORZwhite, and the number of horizontal white lines VERTwhite. And are calculated. Then, the processing unit 30 determines whether or not the absolute value of the product of these differences is greater than a second predetermined value. The second predetermined value may be a value obtained by multiplying the block size Block_size by the square of the determination rate.
When the absolute value of the product of the above differences is not greater than the second predetermined value (S6208; NO), the processing unit 30 advances the processing to S6210.
If the absolute value of the product of the differences is larger than the second predetermined value (S6208; YES), the processing unit 30 advances the process to S6209.

In S6209, the processing unit 30 determines that the block is a valid block.
In S6210, the processing unit 30 determines that the block is not an effective block but an invalid block.
By making the determination result of S6205 described above YES as an effective block condition, it is possible to exclude blocks with a small number of black lines and white lines in a direction perpendicular to the one-dimensional barcode direction.
By making the determination result of S6208 above YES as an effective block condition, the difference between the number of vertical black lines and the number of horizontal black lines is small, or the difference between the number of vertical white lines and the number of horizontal white lines is small. Blocks can be excluded.
After obtaining the determination result of S6209 or S6210 for each of the plurality of second processing blocks, the processing unit 30 ends the processing of this flowchart and returns to the processing shown in FIG.

Here, the case where the one-dimensional barcode direction is input in S6101 has been described. However, when the one-dimensional barcode direction is not input, the one-dimensional barcode direction is particularly oblique with respect to the vertical and horizontal directions of the image. In some cases, the angle of the scanning line in FIG. 14 is tilted, and black points and white points are counted along a direction perpendicular to and parallel to the direction of the scanning line, respectively.
In addition, when the one-dimensional barcode direction is not input, it may be determined as an effective block in a plurality of directions. In that case, the direction of the scanning line having the larger absolute value of the product of the differences described with reference to S6208 is set as the one-dimensional barcode direction.

<4-3. Determination of one-dimensional barcode area>
In S6300 of FIG. 11, the processing unit 30 determines a one-dimensional bar code that may include a one-dimensional barcode based on the determination result of whether or not each of the plurality of second processing blocks is an effective block. Determine the code area. The module that performs the process of S6300 may correspond to the seventh module of the present disclosure. The determination of the one-dimensional barcode area is performed as follows.
FIG. 16 is a flowchart showing details of processing for determining a one-dimensional barcode area in the image processing apparatus 40. The processing shown in FIG. 16 is performed by the processing unit 30 as a subroutine of S6300 in FIG.

First, in S6310 of FIG. 16, the processing unit 30 sets a counter n for counting the one-dimensional barcode area to 1.
Next, in S6320 of FIG. 16, the processing unit 30 extracts the n-th one-dimensional barcode area.

  FIG. 17 is a flowchart showing details of processing for extracting the n-th one-dimensional barcode area in the image processing apparatus 40. The processing shown in FIG. 17 is performed by the processing unit 30 as a subroutine of S6320 in FIG.

  First, in S6321, the processing unit 30 scans a plurality of second processing blocks included in the second image and searches for one effective block. The processing unit 30 searches in the horizontal direction and the vertical direction starting from this effective block, and associates adjacent effective blocks or partially overlapping effective blocks. When the processing unit 30 associates a plurality of adjacent or partially overlapping effective blocks, the processing unit 30 proceeds to step S6322.

In S6322, the processing unit 30 determines whether or not a plurality of associated effective blocks are equal to or larger than a predetermined size.
When the associated plurality of valid blocks is less than the predetermined size (S6322; NO), the processing unit 30 does not set these valid blocks as the nth one-dimensional barcode area. The processing unit 30 returns the processing to S6321, searches for one effective block different from these effective blocks, and scans a plurality of adjacent or partially overlapping effective blocks from the other effective block as a starting point.
When a plurality of associated effective blocks are equal to or larger than the predetermined size (S6322; YES), the processing unit 30 sets these effective blocks as the nth one-dimensional barcode area. Thereafter, the processing unit 30 ends the processing of this flowchart and returns to the processing shown in FIG.

  FIG. 18 shows a state in which adjacent or partially overlapping effective blocks are associated. Nine effective blocks from block number (2, 3) to block number (4, 5) are associated.

  In S6340 of FIG. 16, the processing unit 30 determines whether all the one-dimensional barcode areas have been extracted. For example, when all the plurality of second processing blocks included in the second image are scanned, the processing unit 30 determines that all the one-dimensional barcode areas have been extracted.

When all the one-dimensional barcode areas have not been extracted (S6340; NO), the processing unit 30 adds 1 to the value of the counter n and updates the value of n in S6350. Thereafter, the processing unit 30 returns the processing to the above-described S6320 and extracts the n-th one-dimensional barcode area. For example, another one-dimensional barcode area including valid blocks such as block number (1, 8) and block number (2, 9) shown in FIG. 18 is extracted.
When all the one-dimensional barcode areas are extracted (S6340; YES), the processing unit 30 advances the process to S6360.

In S6360, processing unit 30 enlarges the one-dimensional barcode area.
FIG. 19 shows a state where the one-dimensional barcode area is enlarged. For the effective blocks from block numbers (2, 3) to block numbers (4, 5) associated in FIG. 18, one block upward, one block left, and one block right The one-dimensional barcode area has been expanded. The enlargement width is not limited to one block, and may be two blocks.
However, in FIG. 19, only 0.5 blocks are enlarged in the downward direction. This is because if one block is enlarged downward, it overlaps with another one-dimensional barcode area including valid blocks such as block number (1, 8) and block number (2, 9). By such processing, a one-dimensional barcode area in an appropriate range can be determined.
After S6360 in FIG. 16, the processing unit 30 ends the processing of this flowchart and returns to the processing illustrated in FIG. 11.

<4-4. Reading one-dimensional barcode>
In S6400 of FIG. 11, the processing unit 30 cuts out a corresponding area from the first image for each of the n one-dimensional barcode areas determined in S6300. Then, the processing unit 30 reads the one-dimensional barcode using the barcode analysis program 32.
As described above, the one-dimensional barcode is analyzed.

<5. Analysis of 2D barcode>
FIG. 20 is a flowchart showing details of processing for analyzing a two-dimensional barcode in the image processing apparatus 40. The processing shown in FIG. 20 is performed by the processing unit 30 as a subroutine of S6000 in FIG. The processing shown in FIG. 20 is performed based on the image processing program 31 unless otherwise specified.

<5-1. Extraction of second processing block>
First, in S6500 of FIG. 20, the processing unit 30 extracts a plurality of second processing blocks from the second image generated in S5000 of FIG. The second processing block includes a plurality of pixels. The second processing block may have the same number of pixels as the first processing block, or may have a different number of pixels. The number of pixels of the second processing block may be set by the user using the input / output unit 10. In S6500, the second processing blocks may be set so as not to overlap each other. The module that performs the process of S6500 may correspond to the fifth module of the present disclosure.

  FIG. 21 shows a plurality of second processing blocks extracted from the second image in S6500 of FIG. In FIG. 21, each of the plurality of second processing blocks includes 16 pixels of 4 rows × 4 columns. In the following description, the block number (i, j) is specified using the horizontal coordinate i and the vertical coordinate j.

<5-2. Determining whether the block is valid>
In S6600 of FIG. 20, the processing unit 30 determines, for each of the plurality of second processing blocks, whether the block is an effective block. The determination of whether or not the block is an effective block is performed based on, for example, whether or not the block includes a predetermined number or more of black spots. The predetermined number is set in a range of 10% to 50% of the number of pixels in the block. The module that performs the process of S6600 may correspond to the sixth module of the present disclosure.
FIG. 22 shows the determination result as to whether each of the plurality of second processing blocks is an effective block. In FIG. 22, the valid block is indicated by “A” and the invalid block is indicated by “X”.

<5-3. Determination of 2D barcode area>
In S6700 of FIG. 20, the processing unit 30 determines a two-dimensional bar code that may contain a two-dimensional bar code based on the determination result of whether or not the block is an effective block obtained for each of the plurality of second processing blocks. Determine the code area. The module that performs the process of S6700 may correspond to the seventh module of the present disclosure. The two-dimensional barcode area is determined as follows.
FIG. 23 is a flowchart showing details of processing for determining a two-dimensional barcode area in the image processing apparatus 40. The processing shown in FIG. 23 is performed by the processing unit 30 as a subroutine of S6700 in FIG.

First, in S6710 of FIG. 23, the processing unit 30 sets the value of the counter n that counts the two-dimensional barcode area to 1. In addition, the processing unit sets the value of the variable Jmin that stores the leading row number of the two-dimensional barcode area to 1 in the process of determining the two-dimensional barcode area.
Next, in S6720 of FIG. 23, the processing unit 30 extracts the n-th two-dimensional barcode area.

  FIG. 24 is a flowchart showing details of processing for extracting the n-th two-dimensional barcode area in the image processing apparatus 40. The processing shown in FIG. 24 is performed by the processing unit 30 as a subroutine of S6720 in FIG.

  First, in S6721, the processing unit 30 sets a counter m that indicates what line is counted from the first line number Jmin to 0 in order to extract the n-th two-dimensional barcode area. .

Next, in S6722, the processing unit 30 determines whether there are N or more effective blocks in the row of Jmin. The threshold value N may be three or more, for example. The effective block located at the left end of consecutive effective blocks in the row of Jmin is defined as I (m) min, and the effective block positioned at the right end of consecutive effective blocks in the row of Jmin is defined as I (m) max. . In S6722, since the value of m is 0, I (m) min is I (0) min, and I (m) max is I (0) max.
When there are no N or more effective blocks in the row of Jmin (S6722; NO), the processing unit advances the processing to S6728.

In S6728, the processing unit 30 determines whether or not the value of Jmin is larger than a value obtained by subtracting the threshold N from the last row number J of the plurality of second processing blocks included in the second image. .
When the value of Jmin is not larger than the value obtained by subtracting the threshold value N from the final line number J (S6728; NO), the processing unit 30 advances the processing to S6729.

  In S6729, the processing unit 30 adds 1 to the current value of Jmin, updates the value of Jmin, and returns the process to S6721 described above. Thereby, in S6722, it is determined whether there are N or more effective blocks in the next row.

FIG. 25 shows a process of extracting a two-dimensional barcode area. FIG. 25 shows a case where there are three continuous effective blocks in the third row from the top.
In FIG. 24, when there are N or more effective blocks in the row of Jmin (S6722; YES), the processing unit advances the processing to S6723.

In S6723, the processing unit 30 adds 1 to the value of the counter m and updates the value of m.
Next, in S6724, the processing unit 30 determines whether there are M or more effective blocks in the row of Jmin + m. For example, when m = 1, the processing unit 30 counts the number of valid blocks for the row next to the first row number Jmin, and determines whether the number of valid blocks is M or more. The number of valid blocks in S6724 is counted as follows.

First, the effective block I (m−1) min located at the left end of the effective blocks in the immediately preceding Jmin + m−1 row and the effective block I positioned at the right end of the effective blocks in the Jmin + m−1 row. (m-1) With respect to the processing block located between max, if the processing block immediately below is a valid block (A), it is a valid block (B), and if it is an invalid block (X), it is an invalid block. (Y). However, the invalid block (X) immediately below the valid block (A) in the previous Jmin + m−1 row is treated as the valid block (C) only in the Jmin + m row.
Secondly, when the block immediately to the left of the block immediately below I (m−1) min is a valid block (A), this block is also designated as a valid block (B). When effective blocks (A) continue on the left side, all of these continuous effective blocks are set as effective blocks (B).
Similarly, when the block immediately to the right of the block immediately below I (m−1) max is a valid block (A), this block is also designated as a valid block (B). When valid blocks (A) continue on the right side, all these valid blocks are valid blocks (B).
Third, the number of effective blocks (B) or (C) existing in the row of Jmin + m is counted.

In S6724, M effective blocks (B) or (C) may not be consecutive. The threshold value M is, for example, provided that it is N or more and 0.5 or more times the number of effective blocks (B) or (C) in the immediately preceding row of Jmin + m−1.
The effective block (B) or (C) located at the left end of the effective block (B) or (C) in the row of Jmin + m is defined as I (m) min, and the effective block (B) or (C) in the row of Jmin + m Of these, the effective block (B) or (C) located at the right end is defined as I (m) max.
When there are M or more effective blocks (B) or (C) (S6724; YES), the processing unit 30 returns the processing to the above-mentioned S6723, adds 1 to the value of the counter m, and adds M to the next row. It is determined whether there are more than one valid block.
In the example shown in FIG. 25, the number of effective blocks increases to 5 when m = 1, the number of effective blocks increases to 7 when m = 2, and the number of effective blocks increases to 8 when m = 5. Has increased.
When there are no M or more effective blocks (B) or (C) (S6724; NO), the processing unit 30 advances the processing to S6725.
In the example shown in FIG. 25, there are 8 effective blocks when m = 5, whereas the number of effective blocks is reduced to 3 when m = 6. That is, it is less than 0.5 times the number of effective blocks in the immediately preceding row.

In S6725, values of Inmin, Inmax, Jnmin, and Jnmax for specifying the n-th two-dimensional barcode area are calculated as follows.
Of the effective blocks from the 0th line to the (m-1) th line counted from the line number Jmin, the leftmost effective block I (0) min, I (1) min, ..., I (m-1) min The minimum value is Inmin. Note that I (m) min is the leftmost effective block for a row in which there are no M or more effective blocks in S6724, and is not used in S6725.
Of the effective blocks from the 0th line to the (m-1) th line counted from the line number Jmin, the rightmost effective blocks I (0) max, I (1) max, ..., I (m-1) max The maximum value is Inmax. Note that I (m) max is the rightmost effective block for a row in which there are no M or more effective blocks in S6724, and is not used in S6725.
Let line number Jmin be Jnmin.
The line number Jmin + m−1 is Jnmax. Note that Jmin + m is a line in which there are no M or more effective blocks in S6724, and is not used in S6725.

Next, in S6726, the processing blocks (Inmin, Jnmin) to (Inmax, Jnmax) specified by Inmin, Inmax, Jnmin, and Jnmax are determined as determined processing blocks.
Next, in S6727, the processing unit 30 determines whether or not the value of the counter m is N or more.

When the value of the counter m is N or more (S6727; YES), the processing unit 30 sets the block numbers (Inmin-1, Jnmin-1) to (Inmax + 1, Jnmax + 1) as the nth two-dimensional barcode area. . As described above, by expanding the two-dimensional barcode area vertically and horizontally from the determined processing block, it is possible to extract a two-dimensional barcode area in an appropriate range. The enlargement width may not be one block, for example, two blocks or three blocks.
Thereafter, the processing unit 30 ends the processing of this flowchart and returns to the processing shown in FIG.

  When the value of the counter m is not N or more (S6727; NO), since the number of rows in the j direction of the effective block is small, (Inmin, Jnmin) to (Inmax, Jnmax) are not set as the two-dimensional barcode area. In this case, the processing unit 30 returns the process to S6721 described above. Thereby, in S6722, it is determined whether there are N or more effective blocks in the row of Jmin. For the processing blocks (Inmin, Jnmin) to (Inmax, Jnmax) that have already been determined, valid blocks are not determined thereafter. Further, the value of Jmin is not updated when the process returns from S6727 to S6722. If there is a valid block that has not been determined in the line number Jmin, the above-described processing from S6721 to S6726 is performed starting from the valid block.

  In S6728 described above, when the value of Jmin is larger than the value obtained by subtracting the threshold N from the last row number J of the plurality of second processing blocks included in the second image (S6728; YES), Even if 1 is added, there is no valid block of N rows or more in the j direction. In this case, the processing unit 30 ends the process of this flowchart without extracting the n-th two-dimensional barcode area, and returns to the process shown in FIG.

  As shown by the solid thick frame in FIG. 25, block numbers (Inmin-1, Jnmin-1) to (Inmax + 1, Jnmax + 1) are extracted as two-dimensional barcode areas.

  In S6740 of FIG. 23, the processing unit 30 determines whether or not all the two-dimensional barcode areas have been extracted. For example, when it is determined YES in S6728 described above, the processing unit 30 determines that all the two-dimensional barcode areas have been extracted.

When all the two-dimensional barcode areas have not been extracted (S6740; NO), the processing unit 30 adds 1 to the value of the counter n and updates the value of n in S6750. Thereafter, the processing unit 30 returns the processing to the above-described S6720 and extracts the n-th two-dimensional barcode area. In S6750, the value of Jmin is not changed. Therefore, even when the processing is returned to S6720, the n-th two-dimensional barcode area is extracted in order from the previous row of Jmin.
When all the two-dimensional barcode areas are extracted (S6740; YES), the processing unit 30 advances the process to S6760.
FIG. 25 shows that another two-dimensional bar code area indicated by a thick dashed-dotted frame is extracted.

In S6760, when there are a plurality of adjacent two-dimensional barcode areas, the processing unit 30 combines these adjacent two-dimensional barcode areas into one two-dimensional barcode area.
As shown in FIG. 25, an appropriate two-dimensional bar code area indicated by a solid thick frame and a two-dimensional bar code area indicated by a thick one-dot chain line adjacent to the two-dimensional bar code area are combined. A dimension barcode area can be extracted.
After S6760 in FIG. 23, the processing unit 30 ends the processing of this flowchart and returns to the processing illustrated in FIG.

<5-4. Reading 2D barcodes>
In S6900 of FIG. 20, the processing unit 30 reads the two-dimensional barcode for each of the two-dimensional barcode areas determined in S6700. The reading of the two-dimensional barcode is performed as follows.
FIG. 26 is a flowchart showing details of processing for reading a two-dimensional barcode in the image processing apparatus 40. The processing shown in FIG. 26 is performed by the processing unit 30 as a subroutine of S6900 in FIG.

First, in S6901 of FIG. 26, the processing unit 30 cuts out an image whose range is expanded vertically and horizontally around one two-dimensional barcode area from the first image.
FIG. 27A shows an example of a range of an image cut out in S6901 by a one-dot chain line. The range of the image cut out in S6901 is expanded in the upward and downward directions by the same width as the vertical width of the two-dimensional barcode area with respect to the two-dimensional barcode area indicated by the broken line. In each of the right directions, the range is widened by the same width as the horizontal width of the two-dimensional barcode area.
In step S6902, the processing unit 30 sets the value of the counter k indicating the image processing variation to 1.

Next, in S6903, the processing unit 30 processes the image according to the value of the counter k, and generates a third image. The module that performs the process of S6903 may correspond to the eighth module of the present disclosure.
FIG. 27B to FIG. 27E show examples of image processing variations. As shown in FIG. 27 (B), one processing variation may be to enlarge the reading range on the lower left side of the two-dimensional barcode area. The reading range may be enlarged on the left side and the lower side by the same width as the width of the two-dimensional barcode area. Further, as other processing variations, there may be one that expands the reading range on the lower right side of the two-dimensional barcode area, one that expands the reading range on the upper right side, and one that expands the reading range on the upper left side. . In this way, by expanding the reading range in an oblique direction and shifting the center position of the image, the contrast of the image in the horizontal direction or the vertical direction is adjusted, and the barcode analysis program 32 may succeed in reading.
In addition, as shown in FIG. 27C, as another processing variation, there may be an enlarged width of the reading range different from the enlarged width shown in FIG. The reading range may be enlarged on the left side and the lower side by half the width of the two-dimensional barcode area. The processing variations with different enlargement widths are those that expand the reading range on the lower right side of the two-dimensional barcode area, those that expand the reading range on the upper right side, and those that expand the reading range on the upper left side, respectively. There may be.

In addition, as shown in FIG. 27D, as another processing variation, the reading range may be enlarged substantially uniformly in the vertical and horizontal directions. Furthermore, as another processing variation, there may be one in which the expansion width of the reading range is different from that in FIG. For example, the expansion range of the reading range may have eight variations.
In addition, as shown in FIG. 27E, as another processing variation, there may be an image rotated by a predetermined angle. This predetermined angle may have 22 stages of variation in increments of 2 degrees, for example. Furthermore, even if the predetermined angle is the same, processing variations may exist depending on the size of the reading range.
As shown in FIG. 27A, the amount of calculation can be reduced by performing various processes after cutting out the image in S6901, as compared with the case of performing various processes directly from the first image.

In step S6904, the processing unit 30 reads a two-dimensional barcode using the image processed in step S6903 and the barcode analysis program 32. The module that performs the process of S6904 may correspond to the ninth module of the present disclosure.
In step S6905, the processing unit 30 determines whether the two-dimensional barcode has been successfully read. When the reading of the two-dimensional barcode is successful (S6905; YES), the processing unit 30 ends the process of this flowchart. If reading of the two-dimensional barcode is not successful (S6905; NO), the processing unit 30 determines in S6906 whether the counter k has reached the maximum value kmax.

When the counter k does not reach the maximum value kmax (S6906; NO), the processing unit 30 adds 1 to the value of the counter k to update the value k, and processes the image by another processing variation, Attempts to read 2D barcodes.
When the counter k reaches the maximum value kmax (S6906; YES), the processing unit 30 outputs a signal indicating a reading error in S6907 and ends the process of this flowchart.
The processing in FIG. 26 is performed for all the two-dimensional barcode areas extracted in S6700.

<6. Other>
The scope of the present disclosure is set forth in the claims. In addition, the present disclosure includes the following inventions.
[Claim A]
An image processing apparatus including fifth to seventh modules,
The fifth module extracts a plurality of second processing blocks from the second image,
The sixth module determines whether each of the plurality of second processing blocks is an effective block that is likely to include a part of a barcode,
The seventh module may include one barcode in the second image based on the presence positions of the plurality of blocks determined as the effective block among the plurality of second processing blocks. Extract the barcode area with
Image processing device.
[Claim A1]
An image processing apparatus according to claim A,
The fifth module includes the plurality of second processing blocks such that each of the plurality of second processing blocks partially overlaps at least one second processing block of the plurality of second processing blocks. 2 processing blocks are extracted,
Image processing device.
[Claim A2]
An image processing apparatus according to claim A1,
When the data indicating the repetition direction of the light / dark pattern of at least one one-dimensional barcode included in the second image is input to the fifth module, each of the plurality of second processing blocks includes: Extracting the plurality of second processing blocks so as to partially overlap the second processing block in a direction crossing the repetition direction;
Image processing device.
[Claim A3]
An image processing apparatus according to claim A,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of first columns or rows are extracted from the pixel array of the second processing block, and each of the plurality of first columns or rows has a first predetermined direction and a predetermined width. ,
Determining whether each of the plurality of first columns or rows is a white line or a black line;
Whether the second processing block is the effective block based on the number of white lines in the plurality of first columns or rows and the number of black lines in the plurality of first columns or rows. Determine whether or not
Image processing device.
[Claim A4]
An image processing apparatus according to claim A3,
When the data indicating the repetition direction of the light / dark pattern of at least one one-dimensional barcode included in the second image is input, the sixth module determines the repetition direction and the first predetermined direction. Extracting the plurality of first columns or rows to intersect;
Image processing device.
[Claim A5]
An image processing apparatus according to claim A3,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of second rows or columns are extracted from the pixel array of the second processing block, and each of the plurality of second rows or columns has a second predetermined direction intersecting the first predetermined direction. And having the predetermined width,
Determining whether each of the plurality of second rows or columns is a white line or not a white line;
Based on a comparison result of comparing the number of white lines in the plurality of first columns or rows and the number of white lines in the plurality of second rows or columns, the second processing block is determined to be the effective Determine whether it is a block,
Image processing device.
[Claim A6]
An image processing apparatus according to claim A3,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of second rows or columns are extracted from the pixel array of the second processing block, and each of the plurality of second rows or columns has a second predetermined direction intersecting the first predetermined direction. And having the predetermined width,
Determining whether each of the plurality of second rows or columns is a black line or not a black line;
Based on the comparison result of comparing the number of black lines in the plurality of first columns or rows with the number of black lines in the plurality of second rows or columns, the second processing block is Determining whether the block is valid;
Image processing device.
[Claim A7]
An image processing apparatus according to claim A,
The seventh module extracts a plurality of barcode areas by associating adjacent or partially overlapping blocks among the plurality of blocks determined as the effective block,
For each of the plurality of barcode areas, the barcode area is enlarged so as not to overlap other barcode areas of the plurality of barcode areas.
Image processing device.
[Claim B]
An image processing apparatus including seventh to tenth modules,
The seventh module extracts a barcode area that may contain one barcode from the first image;
The eighth module generates a third image including the barcode area from the first image,
The ninth module executes a barcode analysis program on the image generated by the eighth module;
When the barcode analysis by the ninth module fails, the eighth module includes, from the first image, a fourth image including the barcode area and having a range different from the third image. Generate
Image processing device.
[Claim B1]
An image processing apparatus according to claim B,
The eighth module generates the fourth image so that a center position of the third image and a center position of the fourth image are different from each other;
Image processing device.

DESCRIPTION OF SYMBOLS 10 ... Input-output part, 20 ... Imaging part, 30 ... Processing part, 40 ... Image processing apparatus, 50 ... Tray, 51 ... Goods, 52 ... Character, 53 ... Bar code

Claims (13)

An image processing apparatus including first to fourth modules,
The first module extracts a plurality of first processing blocks from a first image, and each of the plurality of first processing blocks includes a plurality of pixels,
The second module calculates, for each of the plurality of first processing blocks, an average value of values indicating gradations of the plurality of pixels;
The third module is based on a plurality of first average values respectively calculated by the second module for a plurality of peripheral blocks located around the block for each of the plurality of first processing blocks. The corrected average value is calculated by correcting the second average value calculated by the second module for the block,
The fourth module includes a value indicating the gradation of each of the plurality of pixels included in the first image and one block of the plurality of first processing blocks, and the pixel is included. Generating a second image based on the corrected average value calculated for the one block;
Image processing device. The image processing apparatus according to claim 1,
The corrected average value calculated by the third module assigns a first weight to the plurality of first average values, and sets a second weight greater than the first weight to the second average value. It is an average value of the plurality of first average values and the second average value calculated by giving,
Image processing device. The image processing apparatus according to claim 1,
The second image is a binary image;
The fourth module includes:
When the value indicating the gradation of each of the plurality of pixels included in the first image is brighter than the corrected average value calculated for the one block including the pixel, the second A pixel corresponding to the pixel in the image is a white point,
When the value indicating the gradation of each of the plurality of pixels included in the first image is darker than the corrected average value calculated for the one block including the pixel, the second A pixel corresponding to the pixel in the image is a black dot.
Image processing device. The image processing apparatus according to claim 1,
An image processing apparatus including fifth to seventh modules;
The fifth module extracts a plurality of second processing blocks from the second image,
The sixth module determines whether each of the plurality of second processing blocks is an effective block that is likely to include a part of a barcode,
The seventh module may include one barcode in the second image based on the presence positions of the plurality of blocks determined as the effective block among the plurality of second processing blocks. Extract the barcode area with
Image processing device. The image processing apparatus according to claim 4,
The fifth module includes the plurality of second processing blocks such that each of the plurality of second processing blocks partially overlaps at least one second processing block of the plurality of second processing blocks. 2 processing blocks are extracted,
Image processing device. The image processing apparatus according to claim 4,
When the data indicating the repetition direction of the light / dark pattern of at least one one-dimensional barcode included in the second image is input to the fifth module, each of the plurality of second processing blocks includes: Extracting the plurality of second processing blocks so as to partially overlap the second processing block in a direction crossing the repetition direction;
Image processing device. The image processing apparatus according to claim 4,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of first columns or rows are extracted from the pixel array of the second processing block, and each of the plurality of first columns or rows has a first predetermined direction and a predetermined width. ,
Determining whether each of the plurality of first columns or rows is a white line or a black line;
Whether the second processing block is the effective block based on the number of white lines in the plurality of first columns or rows and the number of black lines in the plurality of first columns or rows. Determine whether or not
Image processing device. The image processing apparatus according to claim 7,
When the data indicating the repetition direction of the light / dark pattern of at least one one-dimensional barcode included in the second image is input, the sixth module determines the repetition direction and the first predetermined direction. Extracting the plurality of first columns or rows to intersect;
Image processing device. The image processing apparatus according to claim 7,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of second rows or columns are extracted from the pixel array of the second processing block, and each of the plurality of second rows or columns has a second predetermined direction intersecting the first predetermined direction. And having the predetermined width,
Determining whether each of the plurality of second rows or columns is a white line or not a white line;
Based on a comparison result of comparing the number of white lines in the plurality of first columns or rows and the number of white lines in the plurality of second rows or columns, the second processing block is determined to be the effective Determine whether it is a block,
Image processing device. The image processing apparatus according to claim 7,
The sixth module is configured for each of the plurality of second processing blocks.
A plurality of second rows or columns are extracted from the pixel array of the second processing block, and each of the plurality of second rows or columns has a second predetermined direction intersecting the first predetermined direction. And having the predetermined width,
Determining whether each of the plurality of second rows or columns is a black line or not a black line;
Based on the comparison result of comparing the number of black lines in the plurality of first columns or rows with the number of black lines in the plurality of second rows or columns, the second processing block is Determining whether the block is valid;
Image processing device. The image processing apparatus according to claim 4,
The seventh module extracts a plurality of barcode areas by associating adjacent or partially overlapping blocks among the plurality of blocks determined as the effective block,
For each of the plurality of barcode areas, the barcode area is enlarged so as not to overlap other barcode areas of the plurality of barcode areas.
Image processing device. An image processing apparatus including seventh to ninth modules,
The seventh module extracts a barcode area that may contain one barcode from the first image;
The eighth module generates a third image including the barcode area from the first image,
The ninth module executes a barcode analysis program on the image generated by the eighth module;
When the barcode analysis by the ninth module fails, the eighth module includes, from the first image, a fourth image including the barcode area and having a range different from the third image. Generate
Image processing device. The image processing apparatus according to claim 12,
The eighth module generates the fourth image so that a center position of the third image and a center position of the fourth image are different from each other;
Image processing device.