JP4978460B2 - Bar code recognition apparatus and program - Google Patents

Bar code recognition apparatus and program Download PDF

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JP4978460B2
JP4978460B2 JP2007333278A JP2007333278A JP4978460B2 JP 4978460 B2 JP4978460 B2 JP 4978460B2 JP 2007333278 A JP2007333278 A JP 2007333278A JP 2007333278 A JP2007333278 A JP 2007333278A JP 4978460 B2 JP4978460 B2 JP 4978460B2
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barcode
noise
image
contour position
bar
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JP2009157532A (en
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亮子 薄葉
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富士ゼロックス株式会社
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Description

  The present invention relates to a barcode recognition apparatus and program, and more particularly, to improvement of barcode recognition accuracy.

  When a document is digitized, a barcode is often used to associate the document to be digitized with the data of the digitized document. Electronic data including a barcode used for association may be subjected to processing such as dithering or error diffusion when the image reading device is read by a method such as a photo mode. Further, in order to reduce the image size in digitizing a document, the barcode reading process may be performed at a low resolution. In these cases, irregularities may occur on both sides of the bar outline of the barcode read as an image.

Here, for example, FIG. 7 (a) shows a barcode in which the contour is uneven as described above. When this bar code is processed to restore the unevenness of the bar, the bar may become thick as shown in FIG. 7B or the bar as shown in FIG. 7C. Patent Document 1 proposes a technique for decoding a bar code including noise by a process such as applying a filter for removing irregularities appearing around the bar.
Japanese Patent Laid-Open No. 10-171916

  As described above, when processing such as dithering and error diffusion is performed by the above-described method such as the photo mode and a lot of noise is generated in an image including a barcode, or when the resolution of image data including the barcode is low However, there is a problem that the recognition rate is reduced by removing noise on the barcode included in the image data.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a barcode recognition apparatus and program that improve the recognition rate of barcodes represented by image data.

  The invention of claim 1 is a noise removing unit that removes noise from an image in which a barcode is represented; a decoding unit that decodes the barcode represented in the image from which noise has been removed by the noise removing unit; The noise removing means includes contour position determining means for determining the contour position of each bar in the barcode, and noise removal restricting means for restricting noise removal at the contour position determined by the contour position determining means. And the decoding means performs decoding based on an arrangement of bars and spaces read from a plurality of reading lines in the barcode.

  According to a second aspect of the present invention, in the barcode recognition apparatus according to the first aspect, the barcode is represented in a partial area of the image, and the barcode recognition apparatus is represented in a partial area of the image. It further comprises bar code extracting means for extracting the bar code that has been read.

  According to a third aspect of the present invention, in the barcode recognition apparatus according to the first or second aspect, the contour position determination unit is configured to determine whether each portion of the barcode corresponds to an image of a predetermined pattern. The contour position of each bar in the bar code is determined.

  According to a fourth aspect of the present invention, in the barcode recognition apparatus according to the first or second aspect, the contour position determination unit includes pixels in the image to which color information representing the bar of the barcode is attached. The contour position of each bar is determined according to a pixel group in which the number of pixels included in the pixel group is greater than or equal to a predetermined number of pixels among the plurality of pixel groups formed by the above.

  According to a fifth aspect of the present invention, in the barcode recognition apparatus according to the first or second aspect, the contour position determination means includes an edge in each bar in the longitudinal direction of the barcode and an edge in each bar in the other direction. And the contour position of each bar is determined by comparing each edge in the two directions in each part of the image.

  According to a sixth aspect of the present invention, in the barcode recognition apparatus according to the third or fifth aspect, the noise removing unit removes noise according to the determination result each time the contour position determining unit determines each part. It is characterized by.

  According to a seventh aspect of the present invention, in the barcode recognition apparatus according to the fourth aspect, the noise removing unit removes noise according to a pixel group in which the number of pixels included in the pixel group is less than a predetermined number of pixels. It is characterized by that.

  The invention of claim 8 is a computer as noise removing means for removing noise from an image representing a barcode, and decoding means for decoding the barcode represented in the image from which noise has been removed by the noise removing means. The noise removing means limits the outline position determining means for determining the outline position of each bar in the barcode and the removal of noise at the outline position determined by the outline position determining means. Noise elimination limiting means for performing decoding, wherein the decoding means performs decoding based on an arrangement of bars and spaces read from a plurality of reading lines in the barcode.

  According to the first and eighth aspects, the noise removal of the contour position of each bar of the barcode in the image representing the barcode is restricted, and the arrangement of the bar and space of the barcode is read from a plurality of reading lines. Therefore, it is possible to improve the barcode recognition rate by effectively using information generated from the original arrangement of bars and spaces.

  According to the invention of claim 2, when the barcode is represented in a partial region of the image, the region where the barcode is represented is extracted, so that the speed of recognizing the barcode can be improved. .

  According to the invention of claim 3, it is possible to determine the contour position of each bar of the barcode by determining whether or not it corresponds to a predetermined pattern.

  According to the invention of claim 4, the contour of each bar of the barcode is determined by determining whether or not the pixel group has a predetermined number of pixels or more and identifying the pixel group representing each bar of the barcode. The position can be determined.

  According to the invention of claim 5, it is possible to determine the contour position of each bar of the bar code by paying attention to the bar code and an edge caused by noise other than the bar code.

  According to the invention of claim 6, the speed of recognizing the barcode is improved by removing the noise while determining the contour position of each bar of the barcode in each part of the image on which the barcode is represented. be able to.

  According to the invention of claim 7, since noise is removed while determining the contour position of each bar of the barcode, the speed of recognizing the barcode can be improved.

[First embodiment]
Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram showing a hardware configuration and a functional configuration in a barcode recognition apparatus 1 according to an embodiment of the present invention.

  The barcode recognition device 1 includes a control unit 2, a storage unit 3, and a barcode image acquisition unit 4. The barcode recognition apparatus 1 in the present embodiment may be either a hand-held type or a stationary type barcode reader, and may be mounted on an information processing apparatus such as a personal computer. Here, the bar code is a code made up of an array of bars and spaces having a plurality of types of widths, and is identified by the computer.

  The control unit 2 is a program control device such as a CPU (Central Processing Unit). The control unit 2 includes a noise removal unit 21, a barcode extraction unit 22, and a decoding unit 23 as functional blocks, and each function is realized by executing a program according to the embodiment of the present invention. This program may be provided by being stored in various computer-readable information storage media such as a CD-ROM and a DVD-ROM, or may be provided via communication means such as the Internet.

  The storage unit 3 includes a memory element such as a random access memory (RAM) and a read only memory (ROM), a hard disk, and the like. The storage unit 3 stores a program (software) executed by the control unit 2. The storage unit 3 also operates as a work memory that holds various data used in the process of the control unit 2.

  The barcode image acquisition unit 4 is configured by an image scanner or the like. The image scanner includes, for example, a light source such as an LED that irradiates light on a paper medium, and a light receiving element such as a CCD that captures the reflected light. In particular, the barcode image acquisition unit 4 according to the present embodiment selects a photo mode when digitizing a document including an image, and acquires a barcode displayed on the document as binary image data. . When the barcode image acquisition unit 4 acquires a barcode as binary image data, noise is generated due to processing such as dithering and error diffusion. Here, the barcode image is image data in which a barcode to be recognized by the barcode recognition device 1 is represented in at least a partial area. The barcode image acquisition unit 4 acquires a barcode image. The barcode image acquired by the barcode image acquisition unit 4 is provided to the control unit 2 as a target for decoding processing or the like. Further, the barcode image acquisition unit 4 and the control unit 2 may be configured separately to provide image data acquired from the barcode image acquisition unit 4 through a network.

  Next, functions realized by the noise removal unit 21, the barcode extraction unit 22, and the decoding unit 23 included in the control unit 2 of the barcode recognition apparatus 1 will be described.

  The noise removing unit 21 performs processing for removing noise generated in the barcode image acquired by the barcode image acquiring unit 4. FIG. 2 is a diagram illustrating an example of noise generated in a part of the barcode included in the barcode image. These noises are pixels that indicate other than the original arrangement of the bar and space indicated by the barcode. Such noise may occur when a barcode is imaged, or may already occur on the medium on which the barcode is represented. The former occurs, for example, with processing such as dithering and error diffusion when acquiring a barcode represented on a paper medium or the like as binary image data. Further, the removal of noise is a process of adjusting a pixel group determined to be noise by replacement with pixels existing around the noise. This noise removal processing is executed to make it easy to recognize the original arrangement of the barcode.

  And especially in this embodiment, the noise removal part 21 is further comprised including 21 A of outline position determination parts, and the noise removal restriction | limiting part 21B.

  The contour position determination unit 21A determines the contour position of each bar serving as the boundary between the bar and the space constituting the barcode, along with the contour position serving as the boundary between the patterns included in the barcode image. At this contour position, a color difference occurs due to the color information of each pattern. The contour position of each bar of the barcode in the barcode image can be determined by applying a so-called mask processing algorithm to the entire barcode image. Hereinafter, this process will be described in detail.

  In the contour position determination unit 21A, each part constituting the barcode in the barcode image corresponds to one of six types of images having a size of 3 × 3 as shown in FIGS. 3A to 3F, for example. Whether or not the contour position is determined. FIG. 3 shows a 3 × 3 pattern in which at least two of the upper, lower, left and right pixels are connected as black pixels to the central black pixel. In the case of a binarized barcode image, each bar of the barcode is represented by a black pixel group, and the pixels constituting the outline of each bar are connected to each other in at least two places, upper, lower, left and right. . Accordingly, the contour position determination unit 21A determines whether or not all black pixels in the barcode image correspond to a part of a pattern in which at least two pixels of the upper, lower, left, and right are connected as black pixels. Then, the contour position determination unit 21A adjoins the black pixels that are determined to be a part of the pattern adjacent to the white pixels, and defines the boundary that constitutes the extended portion of the black pixel group. It is determined as the pattern contour position.

  In the above description, the contour position determination unit 21A determines the contour position by performing a so-called mask process, but may perform a so-called labeling process. Specifically, the contour position determination unit 21A is provided with a gradation indicating a bar of a barcode in a barcode image, and pixels that form a group by connecting adjacent pixels in at least one of the vertical and horizontal directions. The contour position of each bar of the barcode and other patterns is determined according to whether or not the group is composed of a predetermined number of pixels or more. In the case of a binarized barcode image, each bar is represented by a black pixel group. Therefore, first, the contour position determination unit 21A classifies all black pixels existing on the barcode image into a pixel group constituting a group by connecting pixels adjacent in at least one direction, up and down or left and right. . In general, the number of black pixels constituting the bar of the barcode is larger than the number of black pixels constituting the noise. Therefore, the contour position determination unit 21A determines the black pixel group constituting the bar and other patterns by determining whether or not each classified pixel group is configured with a predetermined number of pixels or more. Further, the contour position determination unit 21A determines a boundary where a black pixel and a white pixel are adjacent to each other in each black pixel group specified as having a predetermined number of pixels or more. Then, the contour position determination unit 21A determines the boundary where the white pixel exists in the outer extension of the black pixel as the contour position of the bar and other patterns.

  The contour position determination unit 21A may determine the contour position by performing so-called edge detection processing. Specifically, the contour position determination unit 21A determines whether or not each bar has a contour position by a process of detecting an edge between the length direction of each bar of the barcode in the barcode image and the other direction. Determine. Here, the length direction of the bar code means a direction (longitudinal direction of the bar code) perpendicular to the direction in which each bar in the bar code extends. An edge refers to a place where a color difference exists in a predetermined direction. FIG. 4 shows an edge in the length direction of the barcode (FIG. 4A) and an edge in the height direction of the barcode (short direction of the barcode) in the image where the barcode exists (FIG. 4B). It is a figure which shows a mode that the process which detects was performed. Further, FIGS. 4C and 4D show the process of detecting the edge in the length direction and the height direction of the barcode executed in FIGS. 4A and 4B, respectively. It is a figure which shows a mode that it applied with the image which a code does not exist. In each figure of FIG. 4, by performing a process for detecting an edge in the length direction or height direction of the barcode on each original image, a place where the edge exists is a black pixel, and a place where the edge does not exist It has been converted to white pixels. As shown in the figure, the ratio of the edge in the length direction to the edge in the height direction is clearly different in the part where each bar of the barcode exists, but in the part where the barcode does not exist, the length is long. The ratio of the presence of the edge in the vertical direction and the edge in the height direction is approximately the same. Therefore, for example, the area of the black pixel obtained by detecting the edge in the longitudinal direction of the barcode in each part obtained by dividing the barcode image into 10 × 10 regions is defined as the amount of edge in the longitudinal direction, The contour position determination unit 21A obtains and compares these areas for each portion by using the area of the white pixel obtained by detecting the edge in the vertical direction as the edge amount in the height direction. Then, the contour position determination unit 21A determines that the edge in the length direction of the barcode exists in a portion where the edge amount in the length direction exceeds the edge amount in the height direction by a predetermined ratio. The contour position of each bar of the barcode and other patterns is determined. The size of each part that partitions the barcode image is at least a size necessary for recognizing a part of the edge in the length direction of the barcode.

  Next, at the time of noise removal processing by the noise removal unit 21, the noise removal restriction unit 21B leaves at least part of the noise present at the contour positions of the bars and other patterns determined by the contour position determination unit 21A. Thus, the noise removal processing by the noise removal unit 21 is limited. The noise removal unit 21 restricts removal of noise at the contour position of each bar while removing noise of the entire barcode, thereby making it easier to recognize the original width of the bar indicated by the barcode. Here, the noise at the contour position is noise existing in contact with the boundary between each bar and each space. For example, an example thereof is displayed in FIG. Further, restricting noise removal is determined by the contour position determination unit 21A when the noise removal unit 21 performs a process of removing noise by uniformly applying a filter such as smoothing to the entire barcode image. In other words, the noise existing at the contour position is not subjected to the noise removal processing by the filter in advance. In addition, for example, the noise removal restriction unit 21B performs noise removal at the contour position by performing the process of removing only noise existing in a portion other than the contour position of each bar determined by the contour position determination unit 21A. It is good also as restricting the removal of. The noise removal restriction by the noise removal restriction unit 21B may be such that, for example, noise existing other than the contour position is identified and removed as the contour position determination unit 21A determines the contour position. In addition, noise removal may be limited by the noise removal unit 21 executing a noise removal process in which noise existing at the contour position is not removed. Or the noise removal part 21 may perform the process in which removal of at least one part of the noise which exists in an outline position is restrict | limited. FIG. 5A shows an example of an image before the noise removing unit 21 removes noise applied to the entire image including the barcode. FIG. 5B illustrates a process in which the noise removing unit 21 removes noise applied to the entire image while limiting noise removal existing in the contour position of a pattern such as a barcode in the image of FIG. An example of an image subjected to is shown.

  Further, when the contour position determination unit 21A determines the contour position according to the above mask processing, the contour position determination unit 21A determines whether each part of the barcode image corresponds to an image of a pattern as shown in FIG. Each time the determination is made, the noise removal unit 21 removes the portion as noise according to the determination result. Specifically, the contour position determination unit 21A determines that the black pixel in the barcode image does not correspond to a part of the pattern in which at least two pixels of the upper, lower, left, and right are connected to the black pixel. The noise removing unit 21 removes the black pixel as noise. If the contour position determination unit 21A determines the contour position according to the labeling process, the noise removal unit 21 determines the pixel according to the pixel group determined by the contour position determination unit 21A to be less than the predetermined number of pixels. Remove groups as noise. Here, for example, if the predetermined number of pixels is 5, the black pixel group composed of less than 5 pixels in the barcode image is removed as noise. Further, by setting the predetermined number of pixels to be larger than the character string described at the bottom of the barcode and smaller than the number of black pixels of the black pixel group constituting the bar, the contour position determination unit 21A While determining the contour position of the bar, the noise removing unit 21 removes these character strings and the like as noise. If the contour position determination unit 21A determines the contour position in accordance with the edge detection process described above, the contour position determination unit 21A determines each part of the barcode image in the length direction and height direction of the barcode. Each time the edge position is compared to determine the contour position of each bar, the noise removal unit 21 removes the portion as noise according to the determination result. Specifically, the noise removing unit 21 removes, as noise, black pixels existing in a portion where the edge amount in the length direction does not exceed a predetermined ratio with respect to the edge amount in the height direction, or the predetermined ratio is set. A pattern that exists at a position that is not determined as the contour position of each bar of the barcode in the portion exceeding is removed as noise. In this way, the contour position determination unit 21A determines the contour position, and the noise removal unit 21 removes the noise of the barcode image so as not to remove the noise at the contour position, thereby removing the noise of the barcode image. The processing becomes efficient, and it becomes easier to extract a barcode from a barcode image from which noise has been removed, leading to an improvement in the speed of barcode recognition.

  The barcode extraction unit 22 extracts a barcode from an image of a region where the barcode is represented in the barcode image from which the noise removal unit 21 has removed noise. The area where the bar code is expressed refers to the range where each bar and space of the bar code can be cut out as an image that can be identified. It is desirable that it is a range that can be cut out without being included. Here, the process of extracting the barcode by the barcode extracting unit 22 has a feature that the barcode is a set of bars arranged side by side in a predetermined direction. It can be applied using known algorithms. Since the dither pattern and the like are removed from the barcode image after noise removal, the barcode is extracted faster than the barcode is extracted from the barcode image before noise removal.

  The decoding unit 23 sets a reading line for reading the arrangement of the bar and the space for the barcode extracted from the barcode image, and line data indicating the arrangement of the bar and the space obtained from the plurality of reading lines. To decode the barcode. This read line is a virtual line drawn in the length direction of the barcode from the start position of the barcode to the end position of the barcode with a width of at least one pixel. The decoding unit 23 acquires line data indicating the arrangement of bars and spaces from information of pixels existing on each reading line of the barcode image, and decodes the barcode according to the line data acquired from the plurality of reading lines. In particular, in the present embodiment, the function of the noise removal restriction unit 21B restricts the removal of noise present at the contour position in each bar of the barcode. Thereby, the unevenness | corrugation of the outline position of each bar will remain in the some reading line used for the decoding process of the decoding part 23. FIG. When decoding a barcode with irregularities in the contour position according to multiple reading lines, a wider variety of line data is obtained than when decoding a barcode with irregularities removed, so that the barcode By effectively utilizing the information of the image, the arrangement of bars and spaces close to the original barcode arrangement can be recognized, leading to an improvement in recognition rate.

  FIG. 6 is a diagram illustrating an example of a flow of noise removal processing that restricts noise removal of the contour positions of bars and other patterns in a barcode image. First, in step S601, noise is removed by adjusting a black pixel that does not correspond to the mask to a white pixel using a 3 × 3 mask as shown in FIG. By this processing, for example, noise due to black pixels that are on the barcode space and not at the contour position of the barcode is removed. Next, in S602, the white pixel of the barcode image from which noise has been removed in S601 is inverted to a black pixel, and the black pixel is inverted to a white pixel. Then, similarly to S601, using a 3 × 3 mask, noise is removed by adjusting black pixels not corresponding to the mask to white pixels (S603). By this processing, for example, noise that is on the bar of the bar code but not at the outline position of the bar code is removed. In step S604, the barcode image is inverted again to black pixels and the black pixels to white pixels to obtain a barcode image from which noise other than the contour position of the bar has been removed. In S605, each black pixel group obtained in S604 is classified and given a name by so-called labeling processing, and the name and the pixels constituting the pixel group are stored in the storage unit 3. In step S606, a process of removing black pixel groups equal to or less than a predetermined number of pixels is performed according to the information on the pixels constituting each pixel group stored in step S605. By the processing in S606, the description of the numeric part of the barcode and the noise that remains without being removed in S602 are further removed.

  In the above description, the barcode image is image data represented in at least a part of the area. However, the barcode image may be image data in which only the barcode to be recognized by the barcode recognition device 1 is displayed. Good. In this case, the noise removing unit 21 performs the noise removing process while determining the barcode contour position and restricting noise removal at the contour position in the same manner as described above. Then, the decoding unit 23 decodes the barcode from which noise other than the contour position is removed.

[Second Embodiment]
In the second embodiment, the barcode extraction unit 22 extracts an image of the area where the barcode is represented from the barcode image before noise removal, and the noise removal unit 21 performs the barcode extraction on the extracted image. Noise is removed while judging the contour position of the code and restricting noise removal at the contour position. In the following, the second embodiment will be described, but description of parts common to the first embodiment will be omitted.

  The barcode extraction unit 22 first extracts the barcode represented in a partial area of the barcode image acquired by the barcode image acquisition unit 4. Specifically, for example, the barcode extracting unit 22 stores the barcode image in the storage unit 3 and covers the entire barcode image regardless of whether or not the bar is in the contour position of each bar. The noise is removed, and the area where the barcode is expressed is detected from the barcode image from which the noise is removed. Further, the barcode extraction unit 22 displays the barcode from which noise has not been removed from the area of the barcode image before noise removal corresponding to the area detected from the barcode image after noise removal. Extract images.

  Specifically, the processing for removing the noise applied to the entire barcode image is uniformly performed on the area where the barcode of the barcode image is displayed and the area where the barcode is not displayed. For example, a smoothing process for removing noise. This smoothing process is a process for applying, for example, an expansion / contraction filter to the entire surface of the image. From the barcode image that has been subjected to the smoothing process, it is easy to determine the area where the barcode is represented, and the possibility that a pattern other than the barcode in the barcode image is determined as the barcode is reduced. . In addition, since the process in which the barcode extracting unit 22 detects the area where the barcode is represented has a feature that the barcode is a set of bars arranged in a predetermined direction, for example, Algorithms known to those skilled in the art, such as pattern matching, can be used.

  The noise removing unit 21 determines the barcode contour position according to the image representing the barcode extracted by the barcode extracting unit 22, and removes noise while restricting noise removal at the contour position.

  In the first and second embodiments described above, when the processing by the noise removing unit 21, the barcode extracting unit 22, or the decoding unit 23 is performed, the barcode image is subjected to rotation adjustment or the like in advance. The image processing may be performed. For example, by rotating and adjusting the barcode image, in the above-described mask processing, labeling processing, and edge detection processing, processing by the noise removing unit 21 can be smoothed, and processing accuracy can be improved.

  In the first and second embodiments described above, the barcode image acquisition unit 4 acquires the barcode as binary image data. However, the barcode image acquisition unit 4 may acquire the barcode as multi-value image data. In this case, for example, the control unit 2 binarizes the multivalued image data provided from the barcode image acquisition unit 4 and is provided to the processing of the image noise removal unit 21 and the like.

It is a functional block diagram which shows the function which the barcode recognition apparatus concerning embodiment of this invention implement | achieves. It is a figure which shows an example of the noise which has generate | occur | produced in a part of barcode image. It is a figure which shows the example of the image of the predetermined pattern for determining the outline position of each bar of a barcode image. It is a figure which shows the example of the image which performed the process which detects an edge. It is a figure which shows an example of the image which performed the process which removes the noise which restrict | limits the noise removal process of the outline position of a barcode, and the area | region where the barcode was represented. It is a figure which shows an example of the flow of the noise removal process in a barcode image concerning embodiment of this invention. It is a figure which shows the example of the barcode which the unevenness | corrugation produced in the outline, and the barcode which performed the process which decompress | restores an unevenness | corrugation.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Barcode recognition apparatus, 2 Control part, 3 Storage part, 4 Barcode image acquisition part, 21 Noise removal part, 21A Contour position determination part, 21B Noise removal restriction part, 22 Barcode extraction part, 23 Decoding part

Claims (8)

  1. Noise removal means for removing noise from the image on which the barcode is represented;
    Decoding means for decoding the barcode represented in the image from which noise has been removed by the noise removing means,
    The noise removing means is
    Contour position determination means for determining the contour position of each bar in the barcode;
    Noise removal restriction means for restricting removal of noise at the contour position determined by the contour position determination means,
    The decoding means decodes based on the arrangement of bars and spaces read from a plurality of reading lines in the barcode.
    A barcode recognition apparatus characterized by the above.
  2. The barcode recognition device according to claim 1,
    The barcode is represented in a partial area of the image,
    The bar code recognition device includes:
    A barcode extracting means for extracting a barcode represented in a partial area of the image;
    A barcode recognition apparatus characterized by the above.
  3. The barcode recognition apparatus according to claim 1 or 2,
    The contour position determining means determines the contour position of each bar in the barcode based on whether each part of the image corresponds to an image of a predetermined pattern;
    A barcode recognition apparatus characterized by the above.
  4. The barcode recognition apparatus according to claim 1 or 2,
    In the image, the contour position determination unit includes a pixel group including a plurality of pixel groups formed by adjacent pixels to which color information representing the barcode bar is provided. According to a pixel group having a predetermined number of pixels or more, the contour position of each bar is determined.
    A barcode recognition apparatus characterized by the above.
  5. The barcode recognition apparatus according to claim 1 or 2,
    The contour position determining means detects an edge in each bar in the longitudinal direction of the barcode and an edge in each bar in the other direction, and compares each edge in the two directions in each part of the image. To determine the contour position of each bar,
    A barcode recognition apparatus characterized by the above.
  6. In the barcode recognition device according to claim 3 or 5,
    The noise removing unit removes noise according to the determination result each time the contour position determining unit determines each part.
    A barcode recognition apparatus characterized by the above.
  7. In the barcode recognition device according to claim 4,
    The noise removing unit removes noise according to a pixel group in which the number of pixels included in the pixel group is less than a predetermined number of pixels.
    A barcode recognition apparatus characterized by the above.
  8. A program for causing a computer to function as a noise removing unit for removing noise from an image on which a barcode is represented, and a decoding unit for decoding the barcode represented on the image from which noise has been removed by the noise removing unit. ,
    The noise removing means is
    Contour position determination means for determining the contour position of each bar in the barcode;
    Noise removal restriction means for restricting removal of noise at the contour position determined by the contour position determination means,
    The decoding means decodes based on the arrangement of bars and spaces read from a plurality of reading lines in the barcode.
    A program characterized by that.
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JPH07107689B2 (en) * 1988-07-13 1995-11-15 松下電器産業株式会社 Image signal processing device
JPH0896059A (en) * 1994-09-28 1996-04-12 Toshiba Corp Bar code reader
JPH10105640A (en) * 1996-09-27 1998-04-24 Hitachi Ltd Mark reader
JP3635829B2 (en) * 1996-12-10 2005-04-06 松下電器産業株式会社 Bar code reader
JP3726653B2 (en) * 2000-07-27 2005-12-14 ノーリツ鋼機株式会社 Image processing method, image processing apparatus, and recording medium on which program for executing image processing method is recorded

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