JP2015176425A - Bar code reading device, bar code reading method, and bar code reading program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve minimum resolution of bar code reading without increasing the number of pixels of an image sensor for bar code reading.SOLUTION: A bar code reading device includes a processor for binarizing an image-capture image for each pixel according to reception light intensity of each pixel of an image sensor image-capturing the bar code. The processor determines that there exist boundaries of a white part and a black part of the bar code within an object pixel when the reception light intensity of the object pixel of the binarization process assumes an intermediate value between a first reception intensity when one whole pixel is equivalent to the white part of the bar code and a second reception light intensity when one whole pixel is equivalent to a black part of the bar code, and a black and white order inside the object pixel and the boundary position is determined based on the object pixel and the increase/decrease relation of the reception light intensity in the adjacent pixel.

Description

  The present invention relates to a barcode reading apparatus, a barcode reading method, and a barcode reading program, and more particularly to a binarization method in barcode reading.

  A bar code reader (hereinafter also referred to as “bar code scanner”) reads bar codes printed on various products or management objects or attached with labels. A bar code is a code that represents numbers, characters, symbols, and the like by lines of various thicknesses and their intervals. In general, the color of the line is black and the color between the lines is white. However, the color is not limited to white and black as long as the color can be distinguished. In the following, the portion of the line that is the dark portion is referred to as “black portion”, and the portion of the line that is the bright portion is referred to as “white portion”.

  The barcode reader includes an image sensor that receives a barcode image. This barcode reader has a limit (minimum resolution) that can detect the width of the white and black portions of the barcode image received by the image sensor. Normally, a barcode including a fine white portion or black portion exceeding the limit cannot properly separate the white portion and the black portion, so that the barcode cannot be read.

  For example, if the pixel of the one-dimensional image sensor mounted on the barcode reader is 1000 pixels and the barcode width that can be read by the barcode reader is 60 mm, the pixel per pixel of the image sensor of the barcode reader In other words, the apparent resolution corresponds to 60 mm / 1000 pixels, that is, 0.06 mm / pixel.

  However, it is practically impossible for the barcode image to be exactly one-to-one with respect to the sensor pixel width, and the boundary between the white portion and the black portion appears as one image on one pixel of the image sensor. Will occur. The light reception intensity at the pixel in this state takes an intermediate value between the light reception intensity when the entire pixel is a white portion and the light reception intensity when the entire pixel is a white portion. In general, when the intermediate value is closer to the received light intensity of the white portion than a certain threshold, it is determined to be white, and when the intermediate value is closer to the received light intensity of the black portion, it is determined to be black. As a result of such processing, the width of the black portion of the original barcode image (hereinafter also referred to as “barcode original image”) is recognized thicker or more finely by the barcode reader, so that the barcode original is recognized. There was an error in the width of the white part and black part after binarization compared to the image. Due to this error, an appropriate width between the white portion and the black portion cannot be detected, and as a result, decoding of the barcode may fail.

  For this reason, generally the width of about 3 pixels of the image sensor, in this example, 0.06mm x 3 = 0.18mm is the limit (that is, the minimum resolution) that can properly separate the white part and the black part. Yes.

  Next, a conventional binarization method for determining a white portion and a black portion for each pixel using a threshold will be described with reference to FIGS. 13 and 14.

  FIG. 13A shows the bar code label 11. The barcode label 11 imitates a barcode in which black and white are arranged at equal intervals with the same width. FIG. 13B shows a part 12 of the barcode label 11. FIG. 13C shows the image sensor 13 having pixels of pixel numbers 0 to 7. Consider a state in which an image of a bar code label is formed on the image sensor 13. When the pixel width of the image sensor 13 is 1, the width of the black portion of the part 12 of the label is 4.2. As shown in FIG. 13C, it is assumed that the black portion of the part 12 of the label is projected over the pixels 1 to 5 of the image sensor 13 as shown by the shaded portion. At this time, the pixel 1 of the image sensor 13 is projected with a white portion of 0.6 and the pixel 5 is projected with a width of 0.2.

  FIG. 13D shows the received light intensity distribution at each pixel 0 to 7 of the image sensor 13 when the received light intensity is 0 when the entire pixel is a black portion and the received light intensity is 1 when the entire pixel is a white portion. It is the graph 14 which showed. In the binarization method of the prior art, a threshold value is provided for this received light intensity distribution, and when the received light intensity exceeds that value, white is set, and when the received light intensity is lower, black is set. In the example of FIG. 13D, the threshold value is set to 0.5 and binarized.

  FIG. 13E shows a white / black pattern 17 obtained by the above binarization. The width of the black portion of the image projected on the image sensor 13 is 4.2, but is 4 in the white / black pattern 17 after the binarization process. At this stage, the error after binarization with respect to the barcode original image becomes −5%. In the example of FIG. 13, since the width of the black portion of the original image 12 is equal to or more than the number of sensor pixels, the error in the width of the black portion after binarization with respect to the original image 12 is relatively small, and binarization is performed with a threshold value of 0.5. The result of this example is data that can be used for subsequent decoding processing.

  On the other hand, consider the case of FIG. FIG. 14A shows a bar code label 21 used in this example. As with the barcode label 11 in FIG. 13A, the barcode label 21 is a barcode in which black and white are arranged at equal intervals with the same width. FIG. 14B shows a part 22 of the barcode label 21. FIG. 14C shows an image sensor 23 having pixels with pixel numbers 0 to 7. Consider a state in which an image of a bar code label is formed on the image sensor 23. When the width of one pixel of the image sensor 23 is 1, the width of the black portion of the part 22 of the label is 1.4. As shown in FIG. 14C, it is assumed that the black portion of the part 22 of the label is projected as shown by the shaded portion.

  FIG. 14D shows the received light intensity distribution at each pixel 0 to 7 of the image sensor 23 when the received light intensity is 0 when the entire pixel is a black portion and the received light intensity is 1 when the entire pixel is a white portion. It is the graph 24 which showed. In the example of FIG. 14D, the threshold is set to 0.5 and binarized.

  FIG. 14E shows a white / black pattern 27 obtained by the above binarization. When attention is paid to the black portion of the binarized pattern 27, it can be seen that the width 1 and the width 2 are generated. This means that in the original image 22, the black portion having the same width is not identified as the same width after binarization and is nonuniform. In the example of FIG. 14, the black portion that should have the same width of 1.4 has a width of 1 or 2, and has an error of −30% and + 43% with respect to the original image, respectively. In addition, when the binarized state is used as a reference, the width 1 can be the width 2, that is, the error is 100%. This cannot be used in the subsequent decoding process (decoding fails without fail even if the process is performed as it is).

In order to technically solve this problem, a general method is to change the image sensor mounted on the barcode reader to one having a larger number of pixels. However, with this method, an image sensor with a large number of pixels is more expensive, and if the amount of pixel data to be processed thereby increases, the cost of hardware increases, such as requiring a higher-performance processor. The problem is that the image sensor itself having a large number of pixels has technical or manufacturing limitations.
Note that Patent Document 1 discloses a method for improving the apparent resolution in an optical information reading apparatus.

Japanese Patent Laid-Open No. 06-251194

  An object of the present invention is to provide a bar code reading apparatus, a bar code reading method, and a bar code reading program in which the minimum resolution is improved without increasing the number of pixels of an image sensor for reading bar codes.

  A barcode reader according to a first aspect of the present invention includes a processor that binarizes a captured image for each pixel according to the received light intensity of each pixel of an image sensor that has captured the barcode, and the processor is binary. If the light reception intensity of the target pixel of the conversion processing takes an intermediate value between the first light reception intensity when the entire pixel corresponds to the white portion of the barcode and the second light reception intensity when it corresponds to the black portion, the target It is determined that there is a boundary between the white portion and the black portion of the barcode in the pixel, and the order of black and white and the boundary in the target pixel based on the relationship between the increase and decrease in received light intensity in the target pixel and its adjacent pixels and the intermediate value The position is determined.

  The barcode reading method according to the second aspect of the present invention includes a step of binarizing a captured image for each pixel in accordance with the received light intensity of each pixel of the image sensor that has captured the barcode, If the light reception intensity of the target pixel of the conversion processing takes an intermediate value between the first light reception intensity when the entire pixel corresponds to the white portion of the barcode and the second light reception intensity when it corresponds to the black portion, the target It is determined that there is a boundary between the white portion and the black portion of the barcode in the pixel, and the order of black and white and the boundary in the target pixel based on the relationship between the increase and decrease in received light intensity in the target pixel and its adjacent pixels and the intermediate value The position is determined.

  A barcode reading program according to a third aspect of the present invention causes a computer to function as means for binarizing a captured image for each pixel in accordance with the received light intensity of each pixel of an image sensor that has captured the barcode. A barcode reading program, wherein the light receiving intensity of the target pixel for binarization processing is a first light receiving intensity when the whole pixel corresponds to a white portion of the barcode and a second when the whole portion corresponds to a black portion. When taking an intermediate value with respect to the received light intensity, it is determined that the boundary between the white portion and the black portion of the barcode exists in the target pixel, and the increase / decrease relationship of the received light intensity between the target pixel and its adjacent pixels The monochrome order and the boundary position in the target pixel are determined based on the value.

  With the above configuration of the present invention, it is possible to provide a barcode reading apparatus, a barcode reading method, and a barcode reading program capable of improving the minimum resolution without increasing the number of pixels of an image sensor for barcode reading.

1 is a perspective configuration diagram illustrating a basic configuration of a barcode reading apparatus according to an embodiment of the present invention. It is explanatory drawing of the binarization method in embodiment of this invention. It is a flowchart of the barcode reading process in the embodiment of the present invention. It is a flowchart of the binarization process in embodiment of this invention. It is a flowchart of the binarization process in embodiment of this invention. The example which applied the binarization method by embodiment of this invention is shown. Another example to which the binarization method according to the embodiment of the present invention is applied will be described. It is explanatory drawing of the reading limit in embodiment of this invention. It is another explanatory drawing of the reading limit in the embodiment of the present invention. It is a graph which shows the light reception intensity with respect to the pixel number of an image sensor. It is a graph which shows the standardized received light intensity. It is a graph which shows the light reception intensity | strength which performed noise removal after normalization. It is explanatory drawing of the binarization method by a prior art, and shows the example with a comparatively small error. It is explanatory drawing of the binarization method by a prior art, and shows an example with a big error.

  Hereinafter, embodiments for carrying out the present invention will be described in detail.

[Configuration of bar code reader]
FIG. 1 shows a basic configuration of a barcode reader according to an embodiment of the present invention. The bar code reader 1 includes an illumination light source 2, a reflection mirror 3, a condenser lens 4, an image sensor 5, and a processor 6. The processor 6 is connected to a line for communicating with the host device. Communication with the host device may be performed wirelessly. The illumination light source 2 irradiates the barcode (or barcode label) 7 with light. The reflection mirror 3 reflects the light reflected by the barcode 7 toward the condenser lens 4. The reflection mirror 3 can be omitted depending on the shape of the barcode reader 1. The condenser lens 4 forms an image of the reflected light from the barcode 7 on the image sensor 5. An optical filter that appropriately passes the irradiation light may be provided together with the condenser lens 4. The image sensor 5 images the barcode 7 and converts the reflected light from the barcode 7 into an electrical signal. The image sensor 5 is not limited to a one-dimensional image sensor, and may be a two-dimensional image sensor, for example. When a two-dimensional image sensor is used, an appropriate pixel column may be selectively used. The processor 6 performs binarization processing of the barcode image from the received light intensity indicated by each pixel of the image sensor 5. The processor 6 may perform a decoding process on the binarized data obtained by the binarization process. By the decoding process, the original information encoded in the barcode is obtained.

  In general, a barcode is composed of a white portion and a black portion having no intermediate color. Therefore, when the received light intensity of one pixel of the image sensor takes an intermediate value between white and black, it is assumed that the boundary between the white portion and the black portion of the barcode is reflected in the pixel. Further, in such a case, in the embodiment of the present invention, it is assumed that the boundary between the white part and the black part in one pixel is always one place. For example, in the example of FIG. 13, the pixel numbers 1 and 5 of the image sensor 13 correspond to this.

  When the received light intensity at one pixel is 1 (that is, the entire pixel is white) or 0 (that is, the entire pixel is black), there is no white / black boundary in the pixel. Here, the received light intensity is standardized so that it is 1 when the entire pixel is white and 0 when the entire pixel is black (the same applies to the following description). For example, if the received light intensity is 1, white 1 and black 0 are recorded, and if the received light intensity is 0, white 0 and black 1 are recorded. In this case, white or black information that is 0 may be omitted for recording. If the white or black information that becomes 0 is not omitted, the subsequent width calculation is “only black or white that becomes 1 and there is no white / black portion that becomes 0 (that is, there is no white / black boundary). ”.

  When the received light intensity of one pixel takes an intermediate value between white and black, that is, when the received light intensity of one pixel is larger than 0 and smaller than 1 when the above normalization is performed, “white and black Only the “intermediate value” cannot determine the arrangement order of white portions and black portions in the pixel (also referred to as “monochrome order” in the present specification and claims). That is, it cannot be determined whether there is a boundary that changes from a white part to a black part or a boundary that changes from a black part to a white part when viewed from the same direction in the pixel. Hereinafter, changing from a white part to a black part may be abbreviated as “white → black”, and changing from a black part to a white part may be abbreviated as “black → white”.

  In the embodiment of the present invention, when the light reception intensity of one pixel takes an intermediate value between white and black, it is assumed that there is a boundary between white and black in the pixel, and the light reception intensity of the pixel is determined based on the pixel adjacent to the pixel. The order of white and black in the pixel is determined depending on whether the value is decreasing or increasing compared to the received light intensity. Hereinafter, a method for determining whether the order of black and white in the pixel is white → black or black → white will be described for each case.

[Case (1): The minimum white width and black width of the original barcode image is wider than one pixel width of the image sensor, and the light receiving intensity takes an intermediate value between white and black in two or more pixels. (If not continuous)

  In this case, the black-and-white order in the pixel having a light reception intensity having a value between white and black can be determined simply. For example, comparing the light reception intensity (size is an intermediate value) of the pixel with the light reception intensity of the previous pixel (that is, one left side or one right side), and if the value decreases, white → black If the number increases, the order of black → white may be determined.

“Previous pixel” means a pixel related to a binarization process that is performed one time before the binarization process for a pixel having a light reception intensity of an intermediate value. For example, in a series of pixel rows of a one-dimensional image sensor, binarization processing including black and white order determination is performed in order from one end (left side) pixel to the other end (right side) pixel. Think about when to go. In this case, when the received light intensity of a certain pixel has an intermediate value, the “previous pixel” is a pixel on the left side. The left and right are assumed for the sake of convenience, and when the binarization process is started from the pixel at the right end, it is natural that the “previous pixel” is the right pixel. is there. In any case, the order of black and white is determined by comparing the received light intensity between the pixel having the intermediate value of the received light intensity and the adjacent pixel to check the increase / decrease state (also referred to as an increase / decrease relationship). Note that the binarization process is not limited to starting from a pixel at the end of a series of pixel columns of the image sensor, and may be started from any pixel in the pixel column.

  “The light reception intensity is reduced compared to the light reception intensity of the previous pixel” means that the light reception intensity of the pixel immediately before the pixel taking “an intermediate value between white and black” is 1, that is, white It means that. A pixel that takes a value between “white and black” is interpreted as a boundary that switches from white to black in the pixel, and the pixel is in the order of white to black as seen from the previous pixel. It can be judged that it is configured.

  This corresponds to, for example, a state in which an intermediate value of white and black is obtained at pixel number 1 in a portion where the barcode original image changes from white to black at the pixel numbers 0, 1, and 2 in FIG. . In the example of the pixel numbers 0, 1, and 2 in FIG. 13C, when attention is paid to the pixel number 1, the light receiving intensity of the previous pixel (one left side), that is, the pixel number 0 is 1. (Drawing (D) in the figure), pixel number 1 corresponds to “the value is reduced compared to the light reception intensity of the previous pixel”. For this reason, in the above-described way of thinking, the order of white / black of the pixel number 1 can be determined as white → black.

  Next, “the value increases compared with the light reception intensity of the previous pixel” means that the light reception intensity of the pixel immediately before the pixel taking “an intermediate value between white and black” is 0, In other words, it means black. A pixel that takes a value between “white and black” is interpreted as a boundary that switches from black to white in the pixel, and the pixel is black → white in the order of the previous pixel. It can be judged that it is configured.

  This corresponds to a state in which an intermediate value between white and black is obtained at pixel number 5 in a portion where the barcode original image changes from black to white at the pixel numbers 4, 5, and 6 in FIG. In the example of the pixel numbers 4, 5, and 6 in FIG. 13, when attention is focused on the pixel number 5, the light reception intensity of the previous pixel (one left side), that is, the pixel number 4 is 0 (same figure). (D)), the pixel number 5 corresponds to “the value has increased compared to the light reception intensity of the previous pixel”. For this reason, the order of white / black of the pixel number 5 can be determined from black to white based on the above-described concept.

  "When the minimum white width and black width of the barcode original image are wider than one image sensor pixel width and the light receiving intensity takes a value intermediate between white and black does not continue for two or more pixels" In the case (1), since two or more pixels that literally take an “intermediate value between white and black” are not consecutive, attention is paid only to the increase or decrease in the received light intensity at the pixel taking the “intermediate value between white and black”. However, it is not necessary to consider the case of “no increase / decrease”. In the case of “no increase / decrease”, for example, the processing may be incorporated into the processing when the received light intensity increases or decreases.

  Table 1 summarizes the method of determining the black and white order in case (1). In Table 1, when the pixel at the current position has a light reception intensity of an intermediate value between white and black, depending on whether the light reception intensity is increased or decreased with respect to the light reception intensity of the previous adjacent pixel, This shows the white / black pattern of the black-and-white order in this pixel when viewed from the previous pixel.

[Case (2): The minimum white width and black width of the original barcode image is wider than about one pixel width of the image sensor, and the light receiving intensity takes an intermediate value between white and black in two or more pixels. (When consecutive)

  In this case, there is a case where the original barcode image cannot be reproduced correctly only by analyzing the increase / decrease in the received light intensity with the previous pixel. This state corresponds to, for example, pixel numbers 4 and 5 in FIG.

  This problem can be solved by defining the white / black order in the reverse order of the white / black order of the previous pixel. Table 2 summarizes the relationship between the “white / black order of the previous pixel” and the white / black order of the pixel at the current position when the received light intensity of the continuous two pixels is an intermediate value. Table 2 shows the black-and-white order in the direction from the previous pixel to the pixel at the current position for each pixel.

  A process for determining the black and white order in the pixel of pixel number 5 will be described by taking pixel numbers 3, 4, and 5 of FIG. 14C as an example.

First, the pixel of pixel number 3 in FIG. 14C has a light reception intensity of 1, and can be white. Next, since the received light intensity of the pixel of pixel number 4 is 0.4, it can be determined from white to black according to the white / black order correspondence table of the received light intensity increase / decrease in Table 1 described above.

  The pixel No. 5 has a received light intensity of 0.2. Since the previous pixel (pixel number 4) is “a state that takes an intermediate value between white and black (light reception intensity 0.4)”, in pixel numbers 4 and 5, “an intermediate value between white and black continuously” It can be said that this is a state of taking At this time, since the pixel number 4 is determined in the order of “white → black”, the white / black order of the pixel number 5 is the reverse of the white / black order of the pixel number 4, that is, the order of black → white. It can be determined that there is. For pixel numbers 3 to 5, the white / black order determination result is consistent with the state of the original barcode image in FIG.

  In the above-mentioned “case (1): the minimum white width and black width of the barcode original image is wider than one pixel width of the image sensor, and the received light intensity takes an intermediate value between white and black. In the case where “two or more pixels are not continuous”, the width that can be correctly binarized is about two pixels, but in case (2), the minimum width that can be binarized correctly can be improved to about one pixel.

[Case (3): When the first pixel takes an intermediate value between white and black]

  When the first pixel takes an intermediate value between white and black, the previous pixel does not exist, so the order of white → black or black → white cannot be determined by the above-described monochrome determination method. In this case, it is assumed that both white → black and black → white patterns are established in the first pixel. Then, the binarization processing for the second and subsequent pixels is performed under both assumptions, and the method in which a more appropriate result is obtained while the binarization processing is continued or after the binarization processing is completed is adopted.

  Next, how to perform binarization processing according to the monochrome order determination method shown in the above cases (1) to (3) will be described based on a specific example.

  FIG. 2 shows an example in which the binarization process according to the embodiment of the present invention is performed when the original image of the barcode is the same as the original image of FIG. The original image of the barcode in FIG. 2A, the image formation state on the pixels 0 to 7 of the image sensor 33 and the image sensor in FIG. 2B, and the received light intensity distribution in FIG. It is the same as the figure to do.

  FIG. 2D shows the value of the light reception intensity of each pixel (upper stage) and the increase / decrease state (lower stage) obtained by comparing the light reception intensity between each pixel and the previous pixel. The increase / decrease status is described as “+” for increase, “−” for decrease, “=” for no change, and “*” for no comparison (pixel number 0).

  Table 3 summarizes the binarization results for the example of FIG. 2 using the black and white order determination method described above for the pixel numbers 0 to 7 of the image sensor 33.

The binarization process in each pixel in Table 3 will be described.
Pixel number 0: Since the received light intensity is 1, white 1 and black 0 (this means that the pixel width is 1, the white width is 1 and the black width is 0. The same applies hereinafter). Since the received light intensity does not take an intermediate value, branches other than white 1 and black 0 are not considered.
Pixel number 1: received light intensity is 0.6 and a black and white border exists. Since this is the second pixel, only the comparison with the received light intensity of the previous pixel is considered. When the pixel number 0 is compared with the received light intensity, the received light intensity of the pixel 1 is decreased. Therefore, the black-and-white border pattern (black-and-white order) is determined as white → black and becomes white 0.6 and black 0.4 (that is, white width 0.6 and black width 0.4). That is, the boundary between the white portion and the black portion of the barcode exists at a position of 0.6 from the end on the pixel number 0 side in the pixel of pixel number 1. Therefore, the “black and white order” and the “boundary position” are fixed.
Pixel numbers 2, 3, and 4: Since the received light intensity is 0, white 0 and black 1 respectively.
Pixel number 5: received light intensity is 0.2 and a black and white boundary exists. When the received light intensity of the previous pixel (pixel number 4) and the current pixel are compared, it increases. Therefore, the black-and-white boundary pattern is determined in the order of black → white, and becomes black 0.8 and white 0.2.
Pixel numbers 6 and 7: Since the received light intensity is 1, white 1 and black 0 respectively.

  As a result, paying attention to the black portion, the black portion is continuous from pixel 1 to pixel 5 and the width thereof is the sum of the black portion values of pixels 1 to 5, that is, 0.4 + 1.0 + 1.0 + 1.0 + 0.8 = 4.2. Can do. This result coincides with the width of the black portion of the barcode original image 32. FIG. 2E shows a binarized pattern 37 obtained by this method. When this binarized pattern 37 is compared with the binarized pattern obtained by the method according to the prior art (pattern 17 in FIG. 13E), it is obtained by the binarization method of the embodiment of the present invention. It is clear that the pattern after binarization is closer to the original image (in this example, it matches).

  Next, the barcode reading process flow in the embodiment of the present invention will be described with a specific example.

[Hardware configuration and overall processing flow]
As an example, consider the hardware configuration of the barcode reader of FIG. This barcode reader is assumed to have a configuration capable of executing the barcode reading process flow of FIG. The original image of the barcode 7 is projected on the image sensor 5 through the reflecting mirror 3 and the condenser lens 4. In the flow of FIG. 3, the sensor light reception intensity output is acquired from the state imaged on the image sensor 5 (S2) (S3), and binarized from the value (S4). If the binarized information is decoded (S5) and decoding is successful (yes in S6), the decoded data is output (S7) and the processing is terminated (S8), and if decoding fails (S6) no), the process ends without decoding (S8).

  The binarization method according to the embodiment of the present invention is applied to a portion corresponding to the binarization process in step S4 of FIG. FIG. 4 and FIG. 5 show the detailed flow of the binarization process (S4) of the flow of FIG. 4 and 5 are flows based on the embodiment of the present invention (including Tables 1 and 2).

[Specific example 1 of binarization processing]
Hereinafter, a case where the binarization processing according to the embodiment of the present invention is applied to the barcode original image shown in FIG. 14 will be described as an example. This barcode original image is composed of a monochrome pattern having a white portion width of 1.4 and a black portion width of 1.4. The width of each pixel of the image sensor is 1.0.

  As shown in FIG. 14D, in the case of the conventional technique in which the received light intensity of each pixel of the image sensor is binarized by a threshold value 0.5, the binarized pattern 27 differs greatly from the barcode original image 22. As described above.

  FIG. 6 shows a case where the same barcode original image as FIG. 14 is binarized using the method according to the embodiment of the present invention. FIG. 6A shows an original image 42 of the barcode. FIG. 6B shows eight pixels 43 having pixel numbers 0 to 7 in the image sensor, and also shows an image formation state on the image sensor. FIG. 6C is a light reception intensity diagram of each pixel. FIG. 6D shows the value of the light reception intensity of each pixel (upper stage) and the increase / decrease state (lower stage) obtained by comparing the light reception intensity between each pixel and the pixel adjacent to the left. The increase / decrease status is described as “+” for increase, “−” for decrease, and “*” for the first pixel (pixel number 0) not to be compared.

  FIG. 4 shows a detailed flow of the binarization process (step S4 in FIG. 3) in the embodiment of the present invention. When the binarization process is started (S10), first, the received light intensity of the first pixel (= pixel number 0) is acquired (S11). In the example of FIG. 6, the received light intensity of the first pixel of the image sensor is 0.8. Next, it is determined whether the received light intensity is 0 or 1 (S12). In the example of FIG. 6, since the acquired received light intensity is 0.8, the process branches to “no” and proceeds to step S13.

  In step 13, since the order of white and black cannot be determined from the received light intensity of the first pixel (= pixel number 0), a width information group A and a width information group B are provided, and a pending value (P) is set for each. . The width information group A is a data group related to the white part width and black part width of the barcode sequentially obtained from the subsequent pixels on the assumption that the black and white order in the first pixel is white → black (see FIG. 6E). ). The width information group B is a data group relating to the black-and-white pattern of the bar code, the white portion width, and the black portion width, which are sequentially obtained from the subsequent pixels on the assumption that the black and white order in the first pixel is black → white (FIG. 6). (See (F)). The pending value (P) is a value indicating the degree of reliability of the result (binarized data) obtained by performing the binarization process starting from the above assumption, and the smaller the value, the higher the reliability. The width information group is also referred to as a “binarized data group”.

  When the received light intensity is 0 or 1 in step S12, one width information group is provided, and information indicating whether the received light intensity is different from black and white is recorded (S14).

In the example of FIG. 6, in step S14, the width information group A is recorded with pending value (P _A ) = 0, width information of pixel number 0 as white: 0.8 for data number 00 and black: 0.2 for data number 01. Further, in the width information group B, the pending value (P _B ) = 0, the width information of the pixel number 0 is recorded as black: 0.2 in the data number 00 and white: 0.8 in the data number 01, respectively. FIGS. 6E and 6F are images of the binarization at this time. The width information group A is indicated by reference numeral 46 and the width information group B is indicated by reference numeral 47. In step S14, only the pixel 0 portion is recorded.

  Next, the process proceeds to step S15 in FIG. 4, and the received light intensity of the second pixel (= pixel 1), that is, the received light intensity of the pixel of pixel number 1 of the image sensor 43 in FIG. 6B is acquired. The received light intensity obtained at this time is 0.6. In step S16, it is determined whether the acquired received light intensity is 0 or 1. In the example of FIG. 6, since the acquired received light intensity is 0.6, the process proceeds to the “no” flow and proceeds to step S21 of FIG.

  Step S21 in FIG. 5 is a process of “selecting one effective width information group (excluding calculated)”, but since both the width information group A and the width information group B are not calculated, the width information group A is selected first. The process proceeds to step S22. In step S22, it is confirmed whether the light reception intensity of the previous pixel, that is, pixel number 0, is 1 or 0. In the example of FIG. 6, since the received light intensity of the previous pixel, that is, pixel number 0 is 0.8, the process proceeds to the “no” flow in step 22 and proceeds to step S24. By the steps so far, the pixel number 0 and the pixel number 1 indicate that “the received light intensity is an intermediate value between white and black”.

  In step S24, it is confirmed whether or not the determination result of the previous pixel, that is, pixel number 0 in the order of white and black is “black → white”. Since the pixel number 0 of the width information group A is in the order of white → black, “no” is obtained in this flow, and the process proceeds to step S25. In step S25, the white / black order of the pixel currently processed, that is, pixel number 1, is determined as “black → white”, and the process proceeds to step S27.

  In step S27, it is assumed that a black portion having a width of (1−received light intensity value) and a white portion having a width of the received light intensity value are arranged in the order of “black → white” in the pixel of pixel number 1 being currently processed. The sum of the widths of the black portions that straddle the boundary between the previous pixel, that is, the boundary between pixel number 0 and pixel number 1, is calculated. In the example of FIG. 6, since the width of the black portion of pixel number 0 is 0.2 and the width of the black portion of pixel number 1 is 0.4, the total is 0.6, that is, “the total of continuous width information of black is 0.6”. Next, the process proceeds to step S29.

  In step S29, it is confirmed whether the calculation result is 1 or more. In this example, since the result is not 1 or more, the result is “no”, and the process proceeds to step S32.

  In step S32, it is confirmed whether there is another effective width information group. At this time, only the processing of the width information group A is performed. However, since the width information group B exists, “there is another effective width information group”, the process branches to “yes” and proceeds to step S33.

  In step S33, the width information group calculated immediately before, that is, the width information group A is invalidated as inappropriate, and the process returns to step 21 again.

  If it is determined in step S32 that the width of the portion straddling the boundary with the adjacent pixel is in a range less than 1 (also referred to as “discard range”), and no other valid information group exists, step Proceed to S35. In step S35, even if the width of the portion straddling the boundary with the adjacent pixel is less than 1, it is treated as valid and white / black width information is recorded, but at the same time, the pending value (P) is incremented by 1. And record that the credibility level of the data is decreasing.

  When returning from step S33 to step S21, the width information group is selected again in step S21. Here, the uncalculated width information group B is selected. In step S22, the received light intensity acquired in the previous pixel (pixel number 0) is 0.8 and is neither 0 nor 1. Therefore, the process branches to “no” and proceeds to step S24.

  In step S24, since the previous pixel, that is, pixel number 0 of the width information group B is in the order of black → white, “yes” in this flow, the process proceeds to step S26. In step S26, the white / black order of the pixel currently processed, that is, pixel number 1, is determined as “white → black”, and the process proceeds to step S28.

  In step S28, it is assumed that a white portion having a width of the received light intensity value and a black portion having a width of (1−received light intensity value) are arranged in the order of “white → black” in the pixel of pixel number 1 being currently processed. The sum of the widths of the white portions that straddle the boundary between the pixel number 0 and the pixel number 1 is calculated. In the example of FIG. 6, the width of the white portion of pixel number 0 is 0.8 and the width of the white portion of pixel number 1 is 0.6, so the total is 1.4, that is, “the total of white continuous width information is 1.4”. (This is illustrated in FIG. 6F as indicated by reference numeral 47 in FIG. 6). Next, the process proceeds to step S30.

  In step S30, it is confirmed whether the calculation result is 1 or more. Since the result is 1 or more, the answer is “yes” and the process proceeds to step S31. In step S31, white: 0.6 is recorded in data number 02 and black: 0.4 in data number 03 in the order of white → black as the width information of pixel number 1 in width information group B, and the process proceeds to the next step S34. In step S34, it is confirmed whether there is another effective width information group to be processed. In this example, since the information group effective at this stage is only the information group B, the process proceeds to “no” and proceeds to step S18 in FIG.

  In step S18, it is confirmed whether or not the last received light intensity pixel is the last pixel of the image sensor. At this stage, since the next pixel still exists, the process proceeds to “no” and proceeds to step S15.

  In step S15, the received light intensity of the next pixel, that is, the third pixel number 2, is acquired. In the example of FIG. 6, the received light intensity is “0”. In step S16, it is determined whether the received light intensity is 0 or 1. In this example, since the received light intensity is 0, the process proceeds to “yes”, and the process proceeds to step S17.

  In step S17, as a result of the received light intensity of the pixel number 2, the data number 04 is recorded as black: 1 and the data number 05 is recorded as white: 0. The process proceeds to the next step S18, where it is confirmed whether or not the last pixel of received light intensity is the last pixel, and it is determined whether the process returns to step S15 or proceeds to the next.

  Such processing is performed up to pixel number 7 (the last pixel of the image sensor), and if it is determined in step S18 that the pixel is the last pixel, the process proceeds to step S19. At this time, when there are a plurality of effective width information groups, the one having the smallest pending value is selected as a result. In this example, since only the width information group B is valid, the width information group B is selected as a result. In the next step S20, the data of the selected width information group is organized into data that can be used for decoding (binarized data), that is, binarization.

  When the process of step S20 is completed, the process proceeds to the decoding process (S5) of FIG. 3, and the binarized data obtained by the binarizing process is decoded. In the next step S6, it is determined whether or not the decoding is successful. If the decoding is successful (“yes” in S6), the decoding data is output (S7) and terminated (S8), and the decoding must be successful. If it is “no” in S6, the process is terminated as it is (S8).

  Table 4 summarizes specific data of the width information group A and width information group B and binarized data of the width information group B (arranged width data) calculated in this example.

  As a result, the binarized data obtained by the binarization processing on the barcode original image 42 becomes the barcode image 47 shown in FIG. 6F, and a binarization result that matches the barcode original image 42 is obtained. I was able to. Compared with the pattern 27 in FIG. 14E (= the pattern 48 in FIG. 6G) which is the result of binarization by the conventional method, the barcode image reproduced by the binarization processing according to the embodiment of the present invention. Is more accurate.

[Specific example 2 of binarization processing]
Next, a case where the binarization processing according to the embodiment of the present invention is applied to the barcode original image 52 shown in FIG. 7 will be described as an example. The barcode original image 52 is composed of a black and white pattern having a white width of 0.8 and a black width of 0.8. The width of each pixel of the image sensor is 1.0. That is, the white and black widths of the barcode original image reflected on the image sensor are narrower than the pixel widths of the image sensor. FIG. 7G shows a result when binarization is performed by a conventional binarization method with a threshold value of 0.5. Compared to the white / black pattern of the barcode original image 52, the barcode original image 52 has five “black” s having the same width, but the binarized pattern 58 has only three blacks. In addition, it can be said that the width becomes different and cannot be appropriately binarized.

  On the other hand, as in the first specific example, what happens when the binarization processing is performed according to the flow of FIGS. 3, 4, and 5 of the embodiment of the present invention is shown below.

  FIG. 7A shows a barcode original image 52. FIG. 7B also shows an image formation state on the image sensor showing eight pixels 53 of pixel numbers 0 to 7 in the image sensor. FIG. 7C is a light reception intensity diagram of each pixel. FIG. 7D shows the value of the light reception intensity of each pixel (upper stage) and the increase / decrease state (lower stage) obtained by comparing the light reception intensity between each pixel and the pixel adjacent to the left. The increase / decrease status is “+” for increase, “−” for decrease, “=” for equality, and “*” for the first pixel (pixel number 0) not to be compared.

  In the flow of FIG. 3, when it comes to the step (S4) of binarizing the image projected on the image sensor of the barcode reader, the process proceeds to the step (S10) of binarization processing start of FIG. Next, the received light intensity of the first pixel (= pixel number 0) is acquired (S11). In the example of FIG. 7, the received light intensity of the first pixel (= pixel number 0) of the image sensor is 0.2. Next, it is determined whether the received light intensity is 0 or 1 (S12). In the example of FIG. 7, since the acquired light reception intensity is 0.2, the process branches to “no” and proceeds to step S13.

  In step 13, since the order of white / black of the first pixel (= pixel number 0) cannot be determined at this stage, a width information group A and a width information group B are provided, and a pending value (P) is set for each. . The width information group A is a data group related to the white portion width and black portion width of the barcode sequentially obtained from the subsequent pixels on the assumption that the black and white order in the first pixel is white → black (see FIG. 7E). ). The width information group B is a data group relating to the black-and-white pattern of the barcode, the white portion width, and the black portion width, which are sequentially obtained from the subsequent pixels on the assumption that the black and white order in the first pixel is black → white (FIG. 7). (See (F)).

In the example of FIG. 7, in step S14, the width information group A is recorded with pending value (P _A ) = 0, pixel number 0 as white information: data number 00: white: 0.2, data number 01: black: 0.8 In the width information group B, the pending value (P _B ) = 0, the width information of pixel number 0 is recorded as black: 0.2 in data number 00, and white: 0.2 in data number 01. FIG. 7E and FIG. 7F are images of the binarization at this time. The width information group A is indicated by reference numeral 56 and the width information group B is indicated by reference numeral 57. In step S14, only the pixel 0 portion is recorded.

  Next, the process proceeds to step S15 in FIG. 4, and the received light intensity of the second pixel (= pixel 1), that is, the received light intensity of the pixel of pixel number 1 of the image sensor 53 in FIG. 7B is acquired. The received light intensity obtained at this time is 0.6. In step S16, it is determined whether the acquired received light intensity is 0 or 1. In the example of FIG. 7, since the acquired received light intensity is 0.6, the process proceeds to a “no” flow and proceeds to step S21 of FIG.

  Step S21 in FIG. 5 is a process of “selecting one effective width information group (excluding calculated)”, but since both the width information group A and the width information group B are not calculated, the width information group A is selected first. The process proceeds to step S22. In step S22, it is confirmed whether the light reception intensity of the previous pixel, that is, pixel number 0, is 1 or 0. In the example of FIG. 7, since the received light intensity of the previous pixel, that is, pixel number 0 is 0.2, the process proceeds to the “no” flow of step 22 and proceeds to step S24. By the steps so far, the pixel number 0 and the pixel number 1 indicate that “the received light intensity is an intermediate value between white and black”.

  In step S24, it is confirmed whether or not the determination result of the previous pixel, that is, pixel number 0 in the order of white and black is “black → white”. Since the pixel number 0 of the width information group A is in the order of white → black, “no” is obtained in this flow, and the process proceeds to step S25. In step S25, the white / black order of the pixel currently processed, that is, pixel number 1, is determined as “black → white”, and the process proceeds to step S27.

  In step S27, it is assumed that a black portion having a width of (1−received light intensity value) and a white portion having a width of the received light intensity value are arranged in the order of “black → white” in the pixel of pixel number 1 being currently processed. The sum of the widths of the black portions that straddle the boundary between the previous pixel, that is, the boundary between pixel number 0 and pixel number 1, is calculated. In the example of FIG. 7, the width of the black portion of pixel number 0 is 0.8 and the width of the black portion of pixel number 1 is 0.4, so the total is 1.2, that is, “the total of continuous black width information is 1.2”. Next, the process proceeds to step S29.

  In step S29, it is confirmed whether the calculation result is 1 or more. In this example, since the result is 1 or more, “yes” is determined, and the process proceeds to step S31. In step S31, the width information of pixel number 1 of the width information group A is recorded in the order of white → black as white: 0.2 and data number 03 as black: 0.8, and the process proceeds to the next step S34. In step S34, it is confirmed whether there is another effective width information group to be processed. In this example, since the width information group B is not calculated at this stage, the process proceeds to “yes” and returns to step S21.

  In step S21, the width information group is selected again. Here, the uncalculated width information group B is selected. In step S22, the received light intensity acquired by the previous pixel (pixel number 0) is 0.2 and is neither 0 nor 1. Therefore, the process branches to “no” and proceeds to step S24.

  In step S24, since the previous pixel, that is, pixel number 0 of the width information group B is in the order of black → white, “yes” in this flow, the process proceeds to step S26. In step S26, the white / black order of the pixel currently processed, that is, pixel number 1, is determined as “white → black”, and the process proceeds to step S28.

  In step S28, it is assumed that a white portion having a width of the received light intensity value and a black portion having a width of (1−received light intensity value) are arranged in the order of “white → black” in the pixel of pixel number 1 being currently processed. The sum of the widths of the white portions that straddle the boundary between the pixel number 0 and the pixel number 1 is calculated. In the example of FIG. 7, the width of the white part of pixel number 0 is 0.2, and the width of the white part of pixel number 1 is 0.6, so the total is 0.8, that is, “the total of white continuous width information is 0.8”. (This is illustrated by the portion 57 in FIG. 7F). Next, the process proceeds to step S30.

  In step S30, it is determined whether or not the “total of continuous white width information” calculated in step S28 is 1 or more. Since the calculation result is 0.8, step S30 is “no”, and the process proceeds to step S32.

  In step S32, it is confirmed whether there is another effective width information group. In this example, since the width information group A exists, “there is another effective width information group”, the process branches to “yes” and proceeds to step S33. In step S33, the width information group calculated just before, that is, the width information group B is invalidated as inappropriate, and the process returns to step S21 again.

  In step S21, the width information group is selected again. In this example, since there is no width information group to be calculated at this stage, the process proceeds to step S18 in FIG.

  In step S18, it is confirmed whether or not the last received light intensity pixel is the last pixel of the image sensor. At this stage, since the next pixel still exists, the process proceeds to “no” and proceeds to step S15. In step S15, the received light intensity of the next pixel, that is, the third pixel number 2, is acquired. In the example of FIG. 7, the received light intensity is 0.6. In step S16, it is determined whether the received light intensity is 0 or 1. In this example, since the received light intensity is neither 0 nor 1, the process proceeds to "no" and proceeds to step S21.

  Such processing is performed up to pixel number 7 (the last pixel of the image sensor), and if it is determined in step S18 that the pixel is the last pixel, the process proceeds to step S19. At this time, when there are a plurality of effective width information groups, the one having the smallest pending value is selected as a result. In this example, since only the width information group A is valid, the width information group A is selected as a result. In the next step S20, the data of the selected width information group is organized into data that can be used for decoding (binarized data), that is, binarization.

  Table 5 summarizes the specific data of the width information group A and the width information group B calculated in this example and the binarized data (arranged width data) of the width information group A. In the width information group A, the pending value P is increased to 3. The width information group B is discarded at the stage of processing of the second pixel (= pixel 1).

  In this example, an image resulting from binarization according to the embodiment of the present invention is a pattern 56 in FIG. Compared with the image 58 binarized by the conventional method, although the white width and black width of the barcode original image are narrower than the pixel width, the width of 0.8 is accurately reproduced after pixel number 4 The reproducibility of the original image 52 is high. In other words, it means that there is a high possibility of successful decoding in the subsequent decoding process.

  At this time, since it is possible to notify the subsequent decoding processing block that the reproducibility is reduced due to the presence of the pending value during the binarization processing, even if decoding is possible, the reliability of the result is reliable. It is also possible to output a numerical value indicating the degree of decrease.

[Modification of Processing Flow of Embodiment of the Present Invention]
In the binarization method according to FIG. 4 and FIG. 5, the step S29 and the step S30 in FIG. Or, the lower limit value of the black width is set to 1 (= same as the pixel width), and in step S33, if there is another valid candidate, the other is invalidated. Good.

In step S29 and step S30 in FIG. 5, the lower limit value of the white or black width straddling the pixel boundary is set to a range of 0.5 to 1, and the number determined to be “inappropriate” is deliberately lowered and binary Method to leave the processing candidates (width information group) as far as possible. This is effective when the original image has white or black smaller than the pixel width.

Even if it is determined in step S33 that a certain width information group is “inappropriate”, the width information group is not deliberately invalidated, and when all the pixels have been processed, the total of the pending values are compared. The method of adopting the smaller one as “a more reliable result”.

Even if it is determined in step S33 that a certain width information group is “inappropriate”, the width information group is not deliberately invalidated, all pixels are processed, and decoding can be attempted with all binarization results. Among the binarization results, the one with the smallest total pending value is adopted as the “higher reliability result”.

[About reading limit]
As a special example, consider FIG. 8 (A) and FIG. 8 (B). FIG. 8A shows a barcode original image in which white and black having a width of 1 are alternately present, and a white / black boundary is reflected in the center of each pixel. On the other hand, FIG. 8B is a barcode original image in which white and black having a width of 0.5 alternately exist, and a state in which white and black are evenly reflected in each pixel. In both FIG. 8A and FIG. 8B, the results of the received light intensity of all sensor pixels are exactly the same. That is, as a result of the binarization process starting from the value of the received light intensity of the sensor pixel, it cannot be determined whether the original image is FIG. 8 (A) or FIG. 8 (B). Specifically, for each of FIGS. 8A and 8B, when binarization processing is performed in the flow of FIGS. 4 and 5 according to the embodiment of the present invention, both of FIGS. The binarization result is the same as that of the original image, and the original image cannot always be reproduced. This means that the reliability of the binarization processing result is deteriorated in a barcode original image having a white / black width smaller than the pixel width.

  As another special example, consider FIG. 9 (A) and FIG. 9 (B). FIG. 9A shows a white and black pattern with non-uniform width, in which 0.8-width white is partially present. FIG. 9B assumes an original image different from FIG. 9A so that the light reception intensity values of the sensor pixels in FIG. 9A are exactly the same. The original image in FIG. 9B includes 0.4 width white.

  For each of FIGS. 9A and 9B, when binarization processing is performed in the flow of FIGS. 4 and 5 which are embodiments of the present invention, both are the same as the original image of FIG. 9A. The binarization result of This means that among the original images that can be assumed in the binarization process, the original image having a wider white or black width is determined as “more correct”. Although the original image in FIG. 9A can be binarized even if some whites less than the pixel width are included, the original image in FIG. 9B is binarized because it is below the limit width that can be binarized. Cannot be done (the binarized result is the same as the original image in FIG. 9A).

[Pre-processing of sensor light reception intensity]
Actually, the sensor light reception intensity with respect to the original image includes a noise component. Further, since it depends on the printing state of the barcode and the ink state of printing, the white portion does not necessarily become the maximum value of the sensor receivable value, and the black portion does not necessarily become the minimum value of the sensor receivable value. .

  Therefore, consider a state in which a certain original image is reflected on an image sensor having 32 pixels. Assuming that the maximum sensor light receiving value is 1 and the minimum sensor light receiving value is 0, the horizontal axis represents the sensor pixel number and the vertical axis represents the received light intensity as shown in FIG. In FIG. 10, the white portions are distributed in a state including a noise component between 0.6 and 0.8 in terms of the value of received light intensity. Further, the black portion is distributed in a state including a noise component between 0.0 and 0.2 as a value of the received light intensity.

In this state, since it is difficult to use the binarization method according to the embodiment of the present invention, normalization is performed so that the maximum value of the received light intensity of the sensor is 1 and the minimum value is 0. If the sensor pixel number is x, the received light intensity is f (x), the maximum value is f (x) _max , and the minimum value is f (x) _min , the maximum value of the sensor received light intensity is 1 and the minimum value is 0. The value g (x) normalized so that
It becomes. FIG. 11 illustrates g (x). The maximum value can be set to 1 and the minimum value can be set to 0. However, since the noise component remains, it is assumed that the width of 15% of g (x) is noise, and 1 if the value is 0.85 or more. In addition, noise removal is performed by regarding it as 0 if the value is 0.15 or less. The result is shown in FIG. In FIG. 12, the white portion is 1, the black portion is 0, and the boundary thereof takes an intermediate value, which is suitable for binarization processing according to the embodiment of the present invention.

  As described above, the binarization according to the embodiment of the present invention may be performed after pre-processing in a state in which the received light intensity actually acquired by the image sensor is easily binarized.

  In the binarization method in the embodiment of the present invention, the received light intensity of each pixel is analyzed for the barcode captured image captured by the image sensor of the barcode reader, and the received light intensity of the target pixel is the white portion and the black portion. When taking an intermediate value, it is determined that there is a boundary between the white portion and the black portion of the barcode in the pixel, and based on the increase / decrease relationship of the received light intensity between the pixel and the adjacent pixel and the intermediate value Thus, by determining the black and white order and the boundary position within the pixel, binarization with a width smaller than the minimum resolution assumed in the past can be realized.

  Although the conventional bar code reader has a limit that can detect the width of about 3 pixels of the linear image sensor, the bar code reader according to the embodiment of the present invention can also detect the width of about 1 pixel. .

  Note that the above barcode reader can be realized by hardware, software, or a combination thereof. The above barcode reading method can also be realized by hardware, software, or a combination thereof. Here, “realized by software” means realized by a computer reading and executing a program.

  The program may be stored using various types of non-transitory computer readable media and supplied to the computer. Non-transitory computer readable media include various types of tangible storage media. Examples of non-transitory computer readable media include magnetic recording media (for example, flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (for example, magneto-optical disks), CD-ROMs (Read Only Memory), CD- R, CD-R / W, semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (random access memory)). The program may also be supplied to the computer by various types of transitory computer readable media. Examples of transitory computer readable media include electrical signals, optical signals, and electromagnetic waves. The temporary computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.

  A part or all of the above-described embodiment can be described as in the following supplementary notes, but is not limited thereto.

(Appendix 1)
A processor that binarizes the captured image for each pixel in accordance with the light reception intensity of each pixel of the image sensor that has captured the barcode, and the processor has a light reception intensity of the target pixel of the binarization process that is the entire pixel When taking an intermediate value between the first received light intensity corresponding to the white portion of the code and the second received light intensity corresponding to the black portion, a boundary between the white portion and the black portion of the barcode exists in the target pixel. And determining the black-and-white order and the boundary position in the target pixel based on the increase / decrease relationship of the received light intensity in the target pixel and its adjacent pixels and the intermediate value.

(Appendix 2)
When the target pixel has the intermediate value of received light intensity, the processor has a black portion from the adjacent pixel side in the target pixel when the received light intensity of the target pixel is increased with respect to the adjacent pixel. When the received light intensity of the target pixel is reduced with respect to the adjacent pixel, the order of the white portion and the black portion from the adjacent pixel side in the target pixel is determined. The barcode reading apparatus according to appendix 1, wherein the barcode reading apparatus is determined to be disposed at the position.

(Appendix 3)
The processor, when the target pixel and the adjacent pixel have the light reception intensity of the intermediate value, when the black and white order in the adjacent pixel is the order of the black portion and the white portion from the target pixel side, the target In the pixel, it is determined that the black portion and the white portion are arranged in the order from the adjacent pixel side, and when the black and white order in the adjacent pixel is the order of the white portion and the black portion from the target pixel side, the target The barcode reading apparatus according to appendix 1 or 2, wherein it is determined that a white portion and a black portion are arranged in this order from the adjacent pixel side in the pixel.

(Appendix 4)
The processor determines a boundary position between a white portion and a black portion in the target pixel based on a black and white order in the target pixel and a ratio of the received light intensity of the target pixel to the first received light intensity or the second received light intensity. The barcode reader according to any one of appendices 1 to 3, wherein the barcode reader is determined.

(Appendix 5)
When the target pixel is the first pixel in the binarization process, the processor sets a first initial condition in which the black and white order from the adjacent pixel side in the target pixel changes from white to black, and black to white The second initial condition to be changed to tentatively is determined, binarization processing is performed on the subsequent pixels under each of the initial conditions, and each binarized data group is acquired, and based on a predetermined determination criterion The barcode reading apparatus according to any one of appendices 1 to 4, wherein one of the binarized data groups is selected.

(Appendix 6)
The determination criterion is to obtain the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and to binarize the smaller number of the width existing within a predetermined discarding range. The barcode reader according to appendix 5, wherein the data group is selected.

(Appendix 7)
The determination criterion obtains the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and discards the binarized data group whose width is within a predetermined discarding range. The bar code reader according to appendix 5, wherein

(Appendix 8)
An illumination light source for illuminating the barcode;
A condensing lens that focuses the reflected light from the barcode on an image sensor;
An image sensor that measures received light intensity for each pixel with respect to the image of the imaged barcode;
The barcode reader according to any one of appendices 1 to 7, further comprising:

(Appendix 9)
The barcode reading apparatus according to any one of appendices 1 to 8, wherein the processor further performs a decoding process on the binarized data obtained by the binarization process.

(Appendix 10)
The processor obtains the width of the white portion and the black portion of the barcode for each of the obtained two binarized data groups, and performs the decoding based on the number of information whose width is within a predetermined discarding range. The barcode reading apparatus according to supplementary note 9, which cites supplementary note 5, wherein the decoded data having a smaller number is selected from the decoded data obtained by performing the processing.

(Appendix 11)
The processor further normalizes the received light intensity measured at each pixel of the image sensor to have a maximum value of 1 and a minimum value of 0, and considers it as 1 if it is greater than or equal to a predetermined first threshold. The barcode reading apparatus according to any one of appendices 1 to 10, wherein a noise removal process that considers 0 is performed if the second threshold value is less than the second threshold value.

(Appendix 12)
Including a step of binarizing the captured image for each pixel in accordance with the light reception intensity of each pixel of the image sensor that has imaged the barcode, and the light reception intensity of the target pixel of the binarization process in the above step is a bar When taking an intermediate value between the first received light intensity corresponding to the white portion of the code and the second received light intensity corresponding to the black portion, a boundary between the white portion and the black portion of the barcode exists in the target pixel. And determining the black and white order and the boundary position in the target pixel based on the increase / decrease relationship of the received light intensity in the target pixel and its adjacent pixels and the intermediate value.

(Appendix 13)
In the step, when the target pixel has the light reception intensity of the intermediate value, when the light reception intensity of the target pixel is increased with respect to the adjacent pixel, a black portion is formed from the adjacent pixel side in the target pixel. When the received light intensity of the target pixel is reduced with respect to the adjacent pixel, the order of the white portion and the black portion from the adjacent pixel side in the target pixel is determined. 13. The barcode reading method according to appendix 12, wherein the barcode reading method is determined to be arranged in the above manner.

(Appendix 14)
In the step, when the target pixel and the adjacent pixel have the intermediate value of received light intensity, when the black and white order in the adjacent pixel is the order of the black portion and the white portion from the target pixel side, the target In the pixel, it is determined that the black portion and the white portion are arranged in the order from the adjacent pixel side, and when the black and white order in the adjacent pixel is the order of the white portion and the black portion from the target pixel side, the target 14. The barcode reading method according to appendix 12 or 13, wherein in the pixel, it is determined that the white portion and the black portion are arranged in this order from the adjacent pixel side.

(Appendix 15)
In the step, the boundary position between the white portion and the black portion in the target pixel based on the black-and-white order in the target pixel and the ratio of the received light intensity of the target pixel to the first received light intensity or the second received light intensity The barcode reading method according to any one of appendices 12 to 14, wherein the barcode is determined.

(Appendix 16)
In the step, when the target pixel is the first pixel of the binarization process, a first initial condition in which the black and white order from the adjacent pixel side in the target pixel changes from white to black, and black to white The second initial condition to be changed to tentatively is determined, binarization processing is performed on the subsequent pixels under each of the initial conditions, and each binarized data group is acquired, and based on a predetermined determination criterion The barcode reading method according to any one of appendices 12 to 15, wherein one of the binarized data groups is selected.

(Appendix 17)
The determination criterion is to obtain the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and to binarize the smaller number of the width existing within a predetermined discarding range. The barcode reading method according to supplementary note 16, wherein the data group is selected.

(Appendix 18)
The determination criterion obtains the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and discards the binarized data group whose width is within a predetermined discarding range. The barcode reading method according to attachment 16, wherein

(Appendix 19)
Illuminating the barcode with light;
Imaging reflected light from the barcode on an image sensor;
Measuring the received light intensity for each pixel with respect to the image of the imaged barcode;
The barcode reading method according to any one of supplementary notes 12 to 18, further comprising:

(Appendix 20)
The barcode reading method according to any one of appendices 12 to 19, wherein in the binarization processing step, decoding processing is further performed on the binarized data obtained by the binarization processing. .

(Appendix 21)
In the binarization processing step, the width of the white portion and the black portion of the barcode is obtained for each of the obtained two binarized data groups, and the number of the widths existing within a predetermined discarding range is obtained. The barcode reading method according to supplementary note 20 quoting supplementary note 16, wherein the decoded data having the smaller number is selected from the decoded data obtained by performing the decoding process based on the information.

(Appendix 22)
In the binarization processing step, the received light intensity measured at each pixel of the image sensor is normalized so that the maximum value is 1 and the minimum value is 0. The barcode reading method according to any one of appendices 12 to 21, wherein a noise removal process is performed in which it is assumed that the noise is considered to be 1 and 0 if it is equal to or less than a predetermined second threshold value.

(Appendix 23)
A barcode reading program for causing a computer to function as a means for binarizing a captured image for each pixel in accordance with the received light intensity of each pixel of an image sensor that has imaged a barcode. If the light reception intensity of the target pixel of the conversion processing takes an intermediate value between the first light reception intensity when the entire pixel corresponds to the white portion of the barcode and the second light reception intensity when it corresponds to the black portion, the target It is determined that there is a boundary between the white portion and the black portion of the barcode in the pixel, and the order of black and white and the boundary in the target pixel based on the relationship between the increase and decrease in received light intensity in the target pixel and its adjacent pixels A bar code reading program for determining a position.

(Appendix 24)
When the target pixel has the intermediate value of received light intensity, the means has a black portion from the adjacent pixel side in the target pixel when the received light intensity of the target pixel is increased with respect to the adjacent pixel. When the received light intensity of the target pixel is reduced with respect to the adjacent pixel, the order of the white portion and the black portion from the adjacent pixel side in the target pixel is determined. The bar code reading program according to appendix 23, wherein the bar code reading program is determined to be arranged in the above.

(Appendix 25)
In the case where the target pixel and the adjacent pixel have a light reception intensity of the intermediate value, when the black and white order in the adjacent pixel is an order of a black portion and a white portion from the target pixel side, the means In the pixel, it is determined that the black portion and the white portion are arranged in the order from the adjacent pixel side, and when the black and white order in the adjacent pixel is the order of the white portion and the black portion from the target pixel side, the target 25. The barcode reading program according to appendix 23 or 24, wherein the barcode reading program determines that the pixels are arranged in the order of a white portion and a black portion from the adjacent pixel side in the pixel.

(Appendix 26)
The means is configured to determine a boundary position between a white portion and a black portion in the target pixel based on a black and white order in the target pixel and a ratio of the received light intensity of the target pixel to the first received light intensity or the second received light intensity. The barcode reading program according to any one of appendices 23 to 25, wherein the barcode reading program is determined.

(Appendix 27)
When the target pixel is the first pixel in the binarization process, the means includes a first initial condition in which the black and white order from the adjacent pixel side in the target pixel changes from white to black, and black to white The second initial condition to be changed to tentatively is determined, binarization processing is performed on the subsequent pixels under each of the initial conditions, and each binarized data group is acquired, and based on a predetermined determination criterion 27. The barcode reading program according to any one of appendices 23 to 26, wherein one of the binarized data groups is selected.

(Appendix 28)
The determination criterion is to obtain the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and to binarize the smaller number of the width existing within a predetermined discarding range. 28. The bar code reading program according to appendix 27, wherein the data group is selected.

(Appendix 29)
The determination criterion obtains the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and discards the binarized data group whose width is within a predetermined discarding range. The barcode reading program according to supplementary note 27.

(Appendix 30)
The barcode reading program according to any one of appendices 23 to 29, wherein the means further performs a decoding process on the binarized data obtained by the binarization process.

(Appendix 31)
The means further obtains the width of the white portion and the black portion of the barcode for each of the obtained two binarized data groups, and based on the information on the number of the width existing within a predetermined discarding range, The barcode reading program according to supplementary note 30, which cites supplementary note 27, wherein the decoded data having the smaller number is selected from the decoded data obtained by performing the decoding process.

(Appendix 32)
The means further normalizes the received light intensity measured at each pixel of the image sensor to have a maximum value of 1 and a minimum value of 0, and if it is equal to or greater than a predetermined first threshold value, it is regarded as 1. 32. The bar code reading program according to any one of appendices 23 to 31, wherein a noise removal process that considers 0 is performed if the second threshold value is less than the second threshold value.

  The present invention can be used for a part of the binarization program of the barcode reader. As long as the original image has a binary value of white and black, or a bright portion and a dark portion, the present invention can be applied to applications other than the barcode reader.

DESCRIPTION OF SYMBOLS 1 Bar code reader 2 Illumination light source 3 Reflection mirror 4 Condensing lens 5 Image sensor 6 Processor 7 Bar code

Claims (10)

  A processor that binarizes the captured image for each pixel in accordance with the light reception intensity of each pixel of the image sensor that has captured the barcode, and the processor has a light reception intensity of the target pixel of the binarization process that is the entire pixel When taking an intermediate value between the first received light intensity corresponding to the white portion of the code and the second received light intensity corresponding to the black portion, a boundary between the white portion and the black portion of the barcode exists in the target pixel. And determining the black-and-white order and the boundary position in the target pixel based on the increase / decrease relationship of the received light intensity in the target pixel and its adjacent pixels and the intermediate value.   When the target pixel has the intermediate value of received light intensity, the processor has a black portion from the adjacent pixel side in the target pixel when the received light intensity of the target pixel is increased relative to the adjacent pixel. When the received light intensity of the target pixel is reduced with respect to the adjacent pixel, the order of the white portion and the black portion from the adjacent pixel side in the target pixel is determined. The bar code reader according to claim 1, wherein the bar code reader is determined to be disposed at the position.   The processor, when the target pixel and the adjacent pixel have the light reception intensity of the intermediate value, when the black and white order in the adjacent pixel is the order of the black portion and the white portion from the target pixel side, the target In the pixel, it is determined that the black portion and the white portion are arranged in the order from the adjacent pixel side, and when the black and white order in the adjacent pixel is the order of the white portion and the black portion from the target pixel side, the target 3. The barcode reading apparatus according to claim 1, wherein the barcode reading device is determined to be arranged in the order of a white portion and a black portion from a side of the adjacent pixel in the pixel.   The processor determines a boundary position between a white portion and a black portion in the target pixel based on a black and white order in the target pixel and a ratio of the received light intensity of the target pixel to the first received light intensity or the second received light intensity. The barcode reader according to claim 1, wherein the barcode reader is determined.   When the target pixel is the first pixel in the binarization process, the processor sets a first initial condition in which the black and white order from the adjacent pixel side in the target pixel changes from white to black, and black to white The second initial condition to be changed to tentatively is determined, binarization processing is performed on the subsequent pixels under each of the initial conditions, and each binarized data group is acquired, and based on a predetermined determination criterion The bar code reader according to claim 1, wherein one of the binarized data groups is selected.   The determination criterion is to obtain the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and to binarize the smaller number of the width existing within a predetermined discarding range. 6. The barcode reader according to claim 5, wherein a data group is selected.   The determination criterion obtains the width of the white portion and the black portion of the barcode for each of the two acquired binarized data groups, and discards the binarized data group whose width is within a predetermined discarding range. The barcode reader according to claim 5. An illumination light source for illuminating the barcode;
A condensing lens that focuses the reflected light from the barcode on an image sensor;
An image sensor that measures received light intensity for each pixel with respect to the image of the imaged barcode;
The barcode reader according to any one of claims 1 to 7, further comprising:   Including a step of binarizing the captured image for each pixel in accordance with the light reception intensity of each pixel of the image sensor that has imaged the barcode, and the light reception intensity of the target pixel of the binarization process in the above step is a bar When taking an intermediate value between the first received light intensity corresponding to the white portion of the code and the second received light intensity corresponding to the black portion, a boundary between the white portion and the black portion of the barcode exists in the target pixel. And determining the black and white order and the boundary position in the target pixel based on the increase / decrease relationship of the received light intensity in the target pixel and its adjacent pixels and the intermediate value.   A barcode reading program for causing a computer to function as a means for binarizing a captured image for each pixel in accordance with the received light intensity of each pixel of an image sensor that has imaged a barcode. If the light reception intensity of the target pixel of the conversion processing takes an intermediate value between the first light reception intensity when the entire pixel corresponds to the white portion of the barcode and the second light reception intensity when it corresponds to the black portion, the target It is determined that there is a boundary between the white portion and the black portion of the barcode in the pixel, and the order of black and white and the boundary in the target pixel based on the relationship between the increase and decrease in received light intensity in the target pixel and its adjacent pixels and the intermediate value A bar code reading program for determining a position.