JP3971347B2 - Optical information reading method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a method for reading optical information such as a barcode, and more particularly to an optical information reading method suitable for reading optical information displayed on a liquid crystal screen.
[0002]
[Prior art]
Patent Document 1 describes a method of separating and removing a noise component (a noise component caused by dirt or rubbing of a label) included in a read waveform when a barcode is read from a barcode label. . Specifically, in this noise removal method, a step of quantizing the read signal waveform, a step of detecting a peak value of the quantized signal waveform, a step of detecting a wave height difference between the detected peak values, Detecting the difference frequency distribution, detecting the minimum signal peak difference, and deleting the smaller signal peak difference from the signal pattern reading waveform as a reference signal are included in the read waveform. The noise component is removed.
[0003]
[Patent Document 1]
Japanese Patent Laid-Open No. 5-180210
[Problems to be solved by the invention]
In recent years, there has been an increasing need to read optical information (for example, a barcode) displayed on a liquid crystal screen of a terminal device such as a mobile phone. In this case, the liquid crystal screen has dark stripes corresponding to the boundary portions of a large number of pixels in the form of a lattice, so when reading optical information from the liquid crystal screen, due to the influence of the grid-like dark stripes, A relatively large level of noise component is included in the read signal waveform. Such a noise component may be recognized as a thin black bar when the object to be read is a bar code, and may not be decoded. Even when the liquid crystal screen has uneven illumination, a relatively large level of noise component is included in the read signal waveform, and therefore, there is a high possibility that the barcode cannot be decoded. The noise removal method described in Patent Document 1 is effective in removing relatively low level noise, but does not take into account the need to read a barcode displayed on a liquid crystal screen. Therefore, when a relatively large level of noise component is included in the read signal waveform as in the case of reading a bar code displayed on the liquid crystal screen, it is difficult to exert a sufficient noise removal effect. was there.
[0005]
The present invention has been made in view of the above circumstances, and an object thereof is to provide an optical information reading method capable of reliably reading optical information displayed on a liquid crystal screen. .
[0006]
[Means for Solving the Problems]
In the optical information reading method according to claim 1, gray value image data sequentially fetched into a memory in response to a reading operation by the image sensor, that is, gray value image data corresponding to the optical information displayed on the reading surface. The local minimum value and the local maximum value are detected in the order of appearance, and the difference between the adjacent local minimum value and local maximum value is detected as brightness difference data. The detected lightness difference data group is classified for each of the plurality of lightness difference hierarchies, and the frequency distribution of the lightness difference data appearance frequency for each lightness difference hierarchies is detected based on the classification result.
[0007]
Here, when the optical information to be read is, for example, a liquid crystal screen, the image sensor also reads the grid-like dark stripes present on the liquid crystal screen at the same time, and therefore the frequency difference data appearance frequency for each of the above-described brightness difference layers. In the frequency distribution, the lightness difference data corresponding to the pixel boundary portion, that is, the lightness difference data corresponding to the noise component included in the gray value image data has the highest frequency of appearance. The brightness difference data corresponding to the noise component belongs to a brightness difference hierarchy that is relatively smaller than the brightness difference data corresponding to the gray value image data to be read. Therefore, when paying attention to the envelope of the frequency distribution of the brightness difference data appearance frequency, a relatively high peak corresponding to the noise component appears in a region where the brightness difference hierarchy is relatively low, and the brightness difference hierarchy is compared. A peak portion having a relatively small peak corresponding to the optical information to be read appears in the target area.
[0008]
In the optical information reading method according to claim 1, among the peaks formed by the envelope of the frequency distribution of the brightness difference data appearance frequency, the brightness difference data appearance frequency corresponding to the peak of the peak is predetermined. The gray value image data group belonging to the mountain portion that is in a range (for example, a range equal to or less than a preset reference value) and that has a relatively high brightness difference hierarchy is classified as a reading target. For this reason, when the optical information displayed on the liquid crystal screen is read, it is possible to accurately remove the noise component due to the grid-like dark stripes existing on the liquid crystal screen. The gray value image data classified as a reading target as described above is binarized based on a preset threshold value, and analysis processing of the binarized data string is performed. As a result, the optical information displayed on the liquid crystal screen can be reliably read.
[0009]
According to the optical information reading method of claim 2, whether or not the gray value image data group classified as a reading target is appropriate is determined based on whether or not the adjacent local minimum value and local maximum are related to the gray value image data group. Reliability of reading optical information displayed on the liquid crystal screen is checked because it is checked based on the size of the brightness difference data indicating the difference in value and the pitch between the maximum values or the pitch between the minimum values. You can increase your sex.
[0010]
According to the optical information reading method of the third aspect, the series of operations for reading the optical information displayed on the reading surface is performed for each of the divided image areas. Even if there is a variation in the brightness of the reading surface on which the target information is displayed, the adverse effect of the variation on the optical information reading operation can be suppressed.
[0011]
According to the optical information reading method of claim 4, the threshold value necessary for binarizing the gray value image data classified as the reading target is included in the gray image data group classified into the noise components. Therefore, it is possible to prevent a situation in which the binarization processing of gray value image data becomes inaccurate due to noise components.
[0012]
6. The optical information reading method according to claim 5, wherein the threshold value set based on the largest brightness difference data included in the gray image data group divided into noise components is a gray value included in the margin area. Since the adjustment is made based on the level of the image data, the reliability of the binarization processing of the gray value image data can be improved.
[0013]
DETAILED DESCRIPTION OF THE INVENTION
An embodiment of the present invention will be described below with reference to FIGS.
FIG. 4 shows a schematic top view of the barcode reader. In FIG. 4, the barcode reader 1 is provided with an optical head portion 2, a liquid crystal display 3, an operation portion 4 having various keys, and a trigger switch 5. The optical head unit 2 includes an image sensor (shown by reference numeral 7 in FIG. 5 described later) formed of an optical element such as a CCD image sensor or a CMOS image sensor, and an illumination. (Shown with reference numeral 8 in FIG. 5). In this case, the image sensor 7 is configured to convert the barcode (optical information) read from the reading surface into, for example, 256 gray-scale image data and output the data.
[0014]
FIG. 5 schematically shows the electrical configuration of the barcode reader 1 by a combination of functional blocks. As shown in FIG. 5, the bar code reader 1 is configured around a microcomputer 6. In addition to the liquid crystal display 3, the operation unit 4, the trigger switch 5, the image sensor 7, and the illumination unit 8, the microcomputer 6 has an image memory in which gray value image data read by the image sensor 7 is given through the AD conversion unit 9. 10. An input / output interface unit 11 for transmitting / receiving data to / from an external device and a memory 12 for storing various data are connected. Although not shown, the barcode reader 1 has a built-in power supply circuit including a battery for supplying power to the microcomputer 6 and the like.
[0015]
The microcomputer 6 has a function of reading a barcode (optical information) displayed on a liquid crystal screen of a mobile phone or the like by an analysis processing method different from a normal reading operation. This will be described with reference to FIGS.
[0016]
The flowchart of FIG. 1 shows the operation contents when reading the barcode displayed on the liquid crystal screen. That is, when such a reading operation is performed, the trigger switch 5 is operated while the optical head portion 2 of the barcode reader 1 is opposed to the liquid crystal screen on which the barcode is displayed. Then, the gray value image data capturing step S1 shown in FIG. 1 is executed. In this step S1, the image sensor 7 scans the bar code displayed on the liquid crystal screen, and takes in the gray value image data obtained by the scanning into the image memory 10.
[0017]
After this, step S2 (corresponding to the first step in the present invention) of detecting the minimum value and the maximum value of the fetched gray value image data in the order of appearance and storing them in the memory 12 is executed. That is, the gray value image data (256 gradations) captured in the image memory 10 has a lightness gradation that is low in the black background portion of the barcode to be read and a high lightness gradation in the white background portion. Therefore, as shown in FIG. 2, the minimum value and the maximum value appear alternately in the gray value image data when the barcode is read. Of course, the gray value image data also includes a minimum value and a maximum value corresponding to the noise component. In step S <b> 2, the minimum value and the maximum value for such gray value image data are sequentially stored in the memory 12.
[0018]
In FIG. 1 again, after execution of step S2, the difference between adjacent local minimum values and local maximum values among the detected local minimum values and local maximum value groups is sequentially detected as brightness difference data, and the detection results are stored in the memory 12. Step S3 (corresponding to the second step in the present invention) is executed. That is, as shown in FIG. 2 as an example, the difference between the local minimum value and the local maximum value adjacent thereto is the brightness difference data ΔL.
[0019]
Thereafter, step S4 (corresponding to the third step in the present invention) for setting a plurality of levels of brightness difference for classifying the detected brightness difference data group according to the size of each brightness difference data is executed. This brightness difference layer is set, for example, in 32 stages. In this embodiment, since gray value image data has 256 gradations, gray value image data for 8 gradations is stored in each brightness difference layer. Will be included.
[0020]
Next, by classifying the brightness difference data group detected in step S3 for each brightness difference hierarchy set in step S4, step S5 for detecting the frequency distribution of the brightness difference data appearance frequency for each brightness difference hierarchy (in the present invention). Corresponding to the fourth step). That is, in this step S5, a frequency distribution of the brightness difference data appearance frequency as shown in FIG. 3 is created. In FIG. 3, the horizontal axis indicates the brightness difference hierarchy (32 levels), and the vertical axis indicates the brightness difference data appearance frequency.
[0021]
In this case, when the barcode to be read is displayed on the liquid crystal screen as in this embodiment, the image sensor 7 also reads the grid-like dark stripes present on the liquid crystal screen at the same time. In the frequency distribution of the lightness difference data appearance frequency for each lightness difference hierarchy as shown in FIG. 4, the lightness difference data corresponding to the pixel boundary portion in the liquid crystal screen, that is, the lightness difference data corresponding to the noise component included in the gray value image data Appears most frequently. Further, the brightness difference data corresponding to the noise component belongs to a brightness difference hierarchy that is relatively smaller than the brightness difference data corresponding to the gray value image data indicating the barcode to be read. Therefore, when attention is paid to the envelope of the frequency distribution of the brightness difference data appearance frequency, the peak corresponding to the noise component in the area where the brightness difference hierarchy is relatively low (the area where the brightness difference hierarchy is “17” or less in the example of FIG. 3). A relatively large peak appears, and a peak with a relatively small peak appears in a region where the brightness difference hierarchy is relatively high.
[0022]
Therefore, after step S5 is executed, step S6 (corresponding to the fifth step in the present invention) is executed. In this step S6, among the peaks formed by the envelope of the frequency distribution of the brightness difference data appearance frequency (see FIG. 3), a range in which the brightness difference data appearance frequency corresponding to the peak of the peak is determined in advance ( For example, in a peak portion (a range below a reference value set in advance according to the amount of barcode data to be read) and a relatively high brightness difference hierarchy (right peak portion in the example of FIG. 3). The gray value image data group to which it belongs belongs to the reading target, and the gray value image data other than the peak is classified into noise components.
[0023]
Thereafter, step S7 (corresponding to the sixth step in the present invention) for binarizing the gray value image data classified as the reading target based on a preset threshold value is executed. The threshold value is set based on the largest brightness difference data included in the gray image data group classified into noise components in step S6. In the example of FIG. The largest brightness hierarchy difference of the part is “17”, so that “136” obtained by multiplying this by 8 is the largest brightness difference data, and therefore the threshold value is set to “136”. become.
[0024]
The data string binarized in step S7 is used for the subsequent data analysis processing in step S8. In this step S8, the information recorded in the barcode is decoded by decoding the data string. Is to read. Thereafter, step S9 for outputting the analysis result is executed, and the series of bar code reading operations is completed. In step S9, the analysis result is displayed on the liquid crystal display 3 and stored in the memory 12. The analysis result is output to the outside through the input / output interface 11 as necessary. It is.
[0025]
In short, according to the above-described embodiment, when reading the barcode displayed on the liquid crystal screen, the noise caused by the grid-like dark stripes existing on the liquid crystal screen according to the execution of steps S2 to S5. The components can be accurately removed. In addition, the gray value image data classified as the reading target is binarized by a preset threshold value in step S6, and is subjected to an analysis process of the binarized data string. As a result, even if the barcode to be read is displayed on the liquid crystal screen, the barcode can be reliably read.
[0026]
Further, according to the barcode reading method according to the present embodiment, the threshold value necessary for binarizing the gray value image data classified as the reading target in step S6 is classified into noise components in step S6. Since the largest brightness difference data included in the gray image data group is set as a reference, it is possible to prevent a situation in which the binarization processing of gray value image data becomes inaccurate due to noise components.
[0027]
(Other embodiments)
In step S6, for the gray value image data group classified as a reading target, the size of the brightness difference data and the pitch between the maximum values or the pitch between the minimum values are checked, and the size and pitch of the brightness difference data are checked. The gray value image data group can be determined as a reading target when each is within a preset range. That is, in the gray value image data corresponding to the barcode to be read, the magnitude of the brightness difference data should be greater than or equal to a predetermined effective level, and the pitch between the maximum values or the pitch between the minimum values is also Since they should be aligned within a predetermined range, the determination process as described above can be performed using this.
According to such a barcode reading method, whether or not the gray value image data group classified as a reading target is appropriate is a difference between adjacent local minimum values and local maximum values for the gray value image data group. Will be checked on the basis of the lightness difference data and the pitch between the maximum values or the pitch between the minimum values, so the reading operation of the barcode displayed on the LCD screen will be more reliable, The reliability can be improved.
[0028]
Alternatively, a region to be read, that is, an image region corresponding to gray value image data may be divided into a plurality of regions, and steps S2 to S8 may be executed for each of the divided regions. According to such a barcode reading method, since a series of operations for reading the barcode displayed on the liquid crystal screen is performed for each of the divided image areas, the barcode is displayed. Even when the brightness of the liquid crystal screen varies (for example, when the position of the backlight is biased), the adverse effect of the variation on the barcode reading operation can be suppressed.
[0029]
In step S6, a barcode margin area is determined from the frequency distribution feature of the brightness difference data appearance frequency, and the threshold value set in step S7 is based on the level of the gray value image data included in the determined margin area. You may make it perform the step which adjusts a value. Specifically, as shown in FIG. 6 having the same contents as FIG. 2, the area where the change value of the minimum value and the maximum value of the gray value image data is equal to or less than the set value is determined as the margin area of the barcode, and the margin area When the maximum brightness gradation of the gray value image data included in is larger than a set threshold value, the threshold value may be adjusted to be a value larger than the maximum brightness gradation.
According to such a barcode reading method, the threshold value set based on the largest brightness difference data included in the gray image data group divided into noise components is the gray value image data included in the margin area. Therefore, the reliability of the binarization processing of the gray value image data can be improved.
[Brief description of the drawings]
FIG. 1 is a flowchart showing an optical information reading method according to an embodiment of the present invention. FIG. 2 is a diagram showing an example of lightness gradation of gray value image data read by an image sensor. Frequency distribution diagram [FIG. 4] Schematic front view of the barcode reader [FIG. 5] Functional block diagram showing the electrical configuration of the barcode reader [FIG. 6] FIG. ]
1 is a bar code reader, 6 is a microcomputer, 7 is an image sensor, 10 is an image memory, and 12 is a memory.

Claims (5)

The optical information displayed on the reading surface is read by an image sensor and converted into gray value image data. The image data is sequentially taken into a memory, and the gray value image data taken into the memory is binarized. In a method of reading the optical information by performing an analysis process,
A first step of detecting a minimum value and a maximum value of the gray value image data in the order of appearance;
A second step of detecting a difference between adjacent local minimum values and local maximum values among the detected local minimum values and local maximum value groups as brightness difference data;
A third step of setting a plurality of lightness difference hierarchies for classifying the detected lightness difference data group according to the size of each lightness difference data;
A fourth step of detecting the frequency distribution of the brightness difference data appearance frequency for each brightness difference hierarchy by classifying the brightness difference data group for each brightness difference hierarchy;
A fifth step of classifying the gray value image data captured in the memory from a feature of a frequency distribution of the brightness difference data appearance frequency into a noise component and a reading target;
The gray value image data classified as the reading target is binarized based on a preset threshold value, and the sixth step of performing the binarized data string for the analysis processing is executed. And
In the fifth step, among the peaks formed by the envelope of the frequency distribution of the brightness difference data appearance frequency, the brightness difference data appearance frequency corresponding to the peak of the peak is within a predetermined range, An optical information reading method characterized in that a gray value image data group belonging to a mountain portion having a relatively high brightness difference hierarchy is classified as a reading target. In the fifth step, for the gray value image data group classified as a reading target, the size of the brightness difference data and the pitch between the maximum values or the pitch between the minimum values are checked, and the brightness difference data 2. The optical information reading method according to claim 1, wherein the gray value image data group is determined as a reading target when the size and the pitch are within a preset range. 3. The optical information reading according to claim 1, wherein an image area corresponding to the gray value image data is divided into a plurality of areas, and the first to sixth steps are executed for each of the divided areas. Method. The threshold value is set in the fifth step based on the largest brightness difference data included in the gray image data group divided into noise components in the fifth step. 4. The optical information reading method according to any one of 3. The optical information reading method according to claim 4,
In the fifth step, a step of discriminating a margin area of the optical information from the characteristics of the frequency distribution of the brightness difference data appearance frequency, and the level of gray value image data included in the discriminated margin area, Adjusting the set threshold value, and reading the optical information.

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