JP2021015489A - Image analysis device, image analysis system, image analysis method and image analysis program - Google Patents

Abstract

To provide a technology for detecting forgery of a code image.SOLUTION: An image analysis device includes an image reading part for reading an image including a code image to generate image data, an image analysis part for acquiring at least one piece of code information by executing analysis including error correction of the image data, and a forgery determination part for determining that the code image is forged in the case that the at least one piece of code information acquired on the basis of success of the error correction includes a plurality of pieces of mutually different code information.SELECTED DRAWING: Figure 1

Description

The present invention relates to an image analysis technique for detecting forgery of a code image.

In recent years, two-dimensional codes including QR codes (registered trademarks) have become widespread. In the field of image display technology, Patent Document 1 prohibits the transition to the energy saving mode for reducing power consumption when the information storage image (for example, a two-dimensional code) is being displayed, and accompanies the energy saving mode. We are proposing a technology to prevent dimming control that reduces the amount of light from the light source. According to Patent Document 1, according to this technique, it is possible to suppress a situation in which a two-dimensional code cannot be read or is difficult to read due to dimming control.

JP-A-2018-5298

However, sufficient consideration has not been given to the prevention of misuse of code images.

The present invention has been made in view of such a situation, and an object of the present invention is to provide a technique for detecting forgery of a code image.

The image analysis apparatus of the present invention acquires at least one code information by performing an image reading unit that reads an image including a code image and generates image data and an analysis including error correction on the image data. When the image analysis unit and the at least one code information acquired based on the success of the error correction include a plurality of mutually different code information, it is determined that the code image is forged. It is equipped with a counterfeit determination unit.

The image analysis system of the present invention includes the image analysis device and an image display device capable of displaying the code image while changing the light, and the image reading unit is used on the image display device while changing the light. The code image is displayed, the displayed code image is read to generate a plurality of image data, the image analysis unit executes the analysis on each of the plurality of image data, and the counterfeit determination unit , It is determined whether or not the code image is forged for each of the plurality of image data.

The image analysis method of the present invention acquires at least one code information by performing an image reading step of reading an image including a code image to generate image data and an analysis including error correction on the image data. When the at least one code information acquired based on the image analysis step and the success of the error correction contains a plurality of mutually different code information, it is determined that the code image is forged. It is provided with a counterfeit determination step.

The present invention provides an image analysis program for controlling an image analysis device. The image analysis program is an image reading unit that reads an image including a code image to generate image data, and an image analysis unit that acquires at least one code information by executing an analysis including error correction on the image data. , And, when the at least one code information acquired based on the success of the error correction contains a plurality of mutually different code information, the forgery determination unit for determining that the code image is forged. The image analysis device is made to function as.

According to the present invention, it is possible to provide a technique for detecting forgery of a code image.

It is a block diagram which shows the functional structure of the image analysis system 10 which concerns on one Embodiment of this invention. It is a flowchart which shows the content of the 2D code reading process which concerns on a comparative example. It is explanatory drawing which shows the example of the pollution of a 2D code. It is explanatory drawing which shows the example of the density histogram of 2D code QC. It is a flowchart which shows the content of the 2D code reading process which concerns on one Embodiment. It is a flowchart which shows the content of the code information acquisition process which concerns on one Embodiment. It is explanatory drawing which shows the content of the histogram analysis which concerns on one Embodiment. It is a flowchart which shows the content of the forgery determination process which concerns on one Embodiment.

Hereinafter, embodiments for carrying out the present invention (hereinafter, referred to as “embodiments”) will be described with reference to the drawings.

FIG. 1 is a block diagram showing a functional configuration of an image analysis system 10 according to an embodiment of the present invention. The image analysis system 10 includes an image analysis device (smartphone in this example) 100 and a personal computer 200. The image analysis device 100 is configured as, for example, one of the operation modes of a smartphone or tablet. The personal computer 200 may be any one capable of displaying an image, and is also called an image display device.

The image analysis device 100 includes a control unit 110, an operation display unit 130, a storage unit 140, a communication interface unit (also referred to as a communication I / F unit) 150, an image pickup unit 160, and an LED light source 170. There is. The operation display unit 130 functions as a touch panel, displays various menus as input screens, and accepts user operation inputs. The communication interface unit 150 can be connected to a network via Wi-Fi or 4G (wireless communication technology of a fourth-generation mobile phone). The image pickup unit 160 is also called an image reading unit.

The personal computer 200 includes a control unit 210, an operation display unit 230, a storage unit 240, and a communication interface unit (also referred to as a communication I / F unit) 250. The personal computer 200 can be connected to the image analysis device 100 by using the communication interface unit 250.

The imaging unit 160 includes an exposure adjusting unit 161. The exposure adjustment unit 161 can adjust the exposure by operating the shutter speed, the aperture value, and the ISO sensitivity according to the amount of light to be photographed. The shutter speed is the time (exposure time) that the image sensor is exposed to the light that has passed through the optical system. The aperture value is an adjustment amount of the amount of light passing through the optical system, and can be expressed by an F value. The ISO sensitivity corresponds to the amplification factor of the electric signal output from the image sensor. The LED light source 170 is also called a light irradiation unit, and is a light source that can be used for irradiating an imaging target at the time of imaging by the imaging unit 160.

The control unit 110 includes main storage means such as RAM and ROM, and control means such as MPU (Micro Processing Unit) and CPU (Central Processing Unit). In addition, the control unit 110 has controller functions related to interfaces such as various I / O, USB (universal serial bus), bus, and other hardware. The control unit 110 controls the entire image analysis device 100. The control unit 110 further includes an image analysis unit 111, a counterfeit determination unit 113, and a counterfeit response unit 114. The image analysis unit 111 has an error correction unit 112.

The storage unit 140 is a storage device including a hard disk drive, a flash memory, or the like, which are non-temporary recording media, and stores control programs and data for processing executed by the control unit 110, respectively. The storage unit 140 stores an image analysis application program 141 (also simply referred to as an application or an image analysis program) installed to make a smartphone or tablet function as an image analysis device 100.

FIG. 2 is a flowchart showing the contents of the two-dimensional code reading process according to the comparative example. The two-dimensional code reading process is, for example, a process of reading a code image which is an image of a two-dimensional code including a QR code (registered trademark) and acquiring data included in the code image. The QR code (registered trademark) is a code image standardized by JIS (JIS-X-0510). The QR code (registered trademark) comes in 24 sizes from 10 × 10 cells to 144 × 144 cells.

In step S10, the image pickup unit 160 of the image analysis device 100 executes the image pickup process. In this example, the imaging unit 160 captures the printed code image of the two-dimensional code QC with ambient light without turning on the LED light source 170, and generates image data.

FIG. 3 is an explanatory diagram showing an example of contamination of the two-dimensional code. FIG. 3A shows a state in which a stain is attached to the two-dimensional code QC. In this example, the stains are permeable and have varying concentrations. FIG. 3B shows a state in which dirt is attached to the two-dimensional code QC. In this example, the stain is opaque and has varying concentrations. FIG. 3C shows a state in which the two-dimensional code QC is damaged (torn or the like). In this example, the breakage indicates a state in which the base (white) of the article to which the two-dimensional code QC is attached is exposed.

FIG. 4 is an explanatory diagram showing an example of a density histogram of the two-dimensional code QC. In the density histograms H1 and H2, the vertical axis represents the dot frequency, that is, the number of pixels of the image data, and the horizontal axis represents the luminance gradation value. The luminance gradation value is a light amount gradation value, and it is not necessary to consider human vision, and for example, the average of RGB gradation values may be used.

FIG. 4A shows the density histogram H1 as an example of the density histogram of the two-dimensional code QC in the unstained state. In the density histogram H1 in the unstained state, the peak WP1 of the white region constituting the color region of the white cell of the two-dimensional code QC and the peak BP1 of the black region constituting the color region of the black cell of the two-dimensional code QC And are included.

FIG. 4B shows the density histogram H2 as an example of the density histogram of the two-dimensional code QC in the stained state. In the density histogram H2 in the stained state, in addition to the peak WP2 in the white region and the peak BP2 in the black region, the stain of the two-dimensional code QC appears as a stain distribution S having a peak.

In step S20, the image analysis unit 111 of the control unit 110 executes binarization processing on the image data. The image analysis unit 111 executes binarization processing using the threshold value Th1 for the image data representing the two-dimensional code QC in the unstained state. The threshold Th1 is set as an intermediate position between the peak WP2 in the white region and the peak BP2 in the black region of the density histogram H1 in the unstained state. In this example, it is assumed that the image analysis unit 111 employs the mode method for determining the threshold value of the binarization process. That is, the image analysis unit 111 detects a valley in the histogram and uses the value of the valley as a threshold value for binarization processing.

On the other hand, the image analysis unit 111 executes binarization processing using the threshold value Th2 for the image data representing the two-dimensional code QC in the stained state. The threshold Th2 is set in the valley between the peak BP2 in the black region of the density histogram H2 in the stained state and the stain distribution S. As a result, the image analysis unit 111 can execute the binarization process by eliminating the influence of stains caused by stains.

In step S30, the error correction unit 112 of the image analysis unit 111 executes the error correction process. A Reed-Solomon code is adopted as an error correction code for the QR code (registered trademark), and even if a part of the code image is soiled, the data can be restored without losing the data. In the QR code (registered trademark), four levels of error correction levels L, M, Q and H are set, and it is possible to deal with damage in an area of 7%, 15%, 25% and 30% of the code image, respectively. ..

In step S40, if the error correction is successful, the image analysis unit 111 advances the process to step S50, and if the error correction fails, returns the process to the imaging process (step S10) and performs the imaging process (step S10). The process of the error correction process (step S30) is repeated from step S10) (step S40). In this way, the code information is obtained based on the success of error correction.

In step S50, the image analysis unit 111 executes the code information utilization process. In the code information utilization process, the image analysis device 100 can request a connection to the website by using the acquired code information, for example, a URL (Uniform Resource Locator).

FIG. 5 is a flowchart showing the contents of the two-dimensional code reading process according to the embodiment. The two-dimensional code reading process according to one embodiment is different from the two-dimensional code reading process according to the comparative example in that counterfeiting can be detected.

The forgery determination process is performed with an arbitrary probability, for example, hundreds or thousands of times, contrary to the intention of the user of the two-dimensional code, that is, the provider (displayer) of the two-dimensional code and the user (imager) of the two-dimensional code. With a probability of once every time, it is possible to detect counterfeiting to lead to a phishing site instead of a legitimate site. Counterfeiting is realized by utilizing the characteristics of the error correction function adopted in the QR code (registered trademark). The counterfeit determination process is configured by paying attention to the fact that counterfeiting utilizes the characteristics of the error correction function adopted in the QR code (registered trademark).

In step S100, the image pickup unit 160 of the image analysis device 100 executes the image pickup process. The difference between the imaging process (step S100) according to the embodiment and the imaging process (step S10) according to the comparative example will be described later.

FIG. 6 is a flowchart showing the contents of the code information acquisition process (step S200) according to the embodiment. FIG. 7 is an explanatory diagram showing the contents of the histogram analysis according to the embodiment. FIG. 7A shows a density histogram H2 in a stained state (see FIG. 4B). In the density histogram H2, the stains of the two-dimensional code QC appear as a stain distribution S having a peak. FIG. 7B shows a density histogram H3 in a forged state. In the concentration histogram H3, a counterfeit distribution F having a peak due to counterfeit appears.

In step S210, the image analysis unit 111 executes the first binarization process. In the first binarization process, the image analysis unit 111 binarizes the image data representing the two-dimensional code QC in the stained state by using the threshold Th2 (also referred to as the first threshold). Execute the process. The threshold Th2 is set in the valley between the peak BP2 in the black region of the density histogram H2 in the stained state and the stain distribution S. In the present embodiment, it is assumed that the image analysis unit 111 employs the mode method for determining the threshold value of the binarization process.

On the other hand, the image analysis unit 111 executes a binarization process using the threshold value Th4 for the image data representing the two-dimensional code (not shown) in the forged state. The threshold value Th4 (also referred to as a first threshold value) is set as an intermediate position between the peak WP3 in the white region and the peak BP3 in the black region. That is, the image analysis unit 111 did not determine the valley between the peak BP3 in the black region of the density histogram H3 with forgery and the forgery distribution F as an effective valley for setting the threshold value for the binarization process. Alternatively, the peaks and valleys of the counterfeit distribution F were not detected.

In step S220, the error correction unit 112 executes the error correction process. In step S230, the image analysis unit 111 proceeds to the first data acquisition process (step S240) when the error correction is successful, and when the error correction fails, the first data acquisition process (step S240). Step S240) is skipped and the process proceeds to step S250. This is because if the error correction fails, valid code information cannot be obtained.

When the error correction fails, the process is returned to step S100 (see FIG. 5), the process of the imaging process (step S100) to the error correction process (step S220) is repeated, a predetermined number of times or time elapses, and a timeout occurs. (This routine is not shown).

In step S240, the image analysis unit 111 executes the first code information acquisition process. In this example, it is assumed that the image analysis unit 111 succeeds in error correction in both the two-dimensional code QC in the stained state and the two-dimensional code in the forged state, and acquires the data after the error correction processing.

In step S250, the image analysis unit 111 executes the second binarization process. In the second binarization process, the image analysis unit 111 executes the binarization process with a second threshold value different from the first threshold value used in the first binarization process.

In the second binarization process, the image analysis unit 111 binarizes the image data representing the two-dimensional code QC in the stained state by using the threshold value Th3 (also referred to as the second threshold value). Execute the process. The threshold value Th3 is set in the valley between the peak WP2 in the white region of the density histogram H2 in the stained state and the stain distribution S, that is, in the valley that straddles the stain distribution S from the position of the first threshold value.

On the other hand, in the second binarization process, the image analysis unit 111 uses the threshold value Th5 (also referred to as the second threshold value) for the image data representing the two-dimensional code in the forged state to obtain two values. Execute the conversion process. The threshold value Th5 (also referred to as a second threshold value) is set in the valley between the peak BP3 in the black region of the density histogram H3 in the forged state and the counterfeit distribution F. That is, the image analysis unit 111 determines that the valley between the peak BP3 in the black region of the density histogram H3 with counterfeiting and the counterfeit distribution F is an effective valley for setting the threshold value for the binarization process. ..

In step S260, the error correction unit 112 executes the error correction process. In step S270, the image analysis unit 111 proceeds to the second data acquisition process (step S280) if the error correction is successful, and if the error correction fails, the second data acquisition process (step S280). Step S280) is skipped and the process proceeds to step S300 (see FIGS. 5 and 8).

When the error correction fails, the process is returned to step S100 (see FIG. 5), and the imaging process (step S100), the second binarization process (step S250), and the error correction process (step S260) are performed. It means that the time has expired after the predetermined number of times or time has passed repeatedly (this routine is not shown).

In step S280, the image analysis unit 111 executes the second code information acquisition process. In this example, it is assumed that the image analysis unit 111 succeeds in error correction in both the two-dimensional code QC in the stained state and the two-dimensional code in the forged state, and acquires the data after the error correction processing.

FIG. 8 is a flowchart showing the contents of the forgery determination process (step S300) according to the embodiment. The forgery determination process is executed for each of the two-dimensional code QC in the stained state and the two-dimensional code in the forged state.

In step S310, whether or not the forgery determination unit 113 succeeds in error correction in both the case where the binarization process using the first threshold value and the binarization process using the second threshold value are executed. To judge. The counterfeit determination unit 113 proceeds to step S320 if the error correction is successful in both cases, and proceeds to step S340 if only one of them succeeds in error correction.

Specifically, in the case of the two-dimensional code QC with stains, if the error correction is successful in both cases, the influence of the stain distribution S is the second in the binarization process using the first threshold Th2. It is eliminated by the threshold value Th2 of 1, and in the binarization process using the second threshold value Th3, the influence of the stain distribution S is eliminated by error correction. If the error correction is successful on only one side, in the binarization process using the first threshold Th2, the influence of the stain distribution S is eliminated by the first threshold Th2, and the second threshold is used 2 In the valuation process, it is assumed that the influence of the stain distribution S could not be eliminated by error correction. In either case, in the case of the two-dimensional code QC in the soiled state, a single code information is acquired.

On the other hand, in the case of the two-dimensional code with forgery, if the error correction is successful in both cases, the influence of the forgery distribution F is the first threshold Th4 in the binarization process using the first threshold Th4. In the binarization process using the second threshold Th5, there is a possibility that the error correction is successful after being forged into a two-dimensional code representing another code information due to the influence of the forgery distribution F. .. If the error correction is successful on only one side, in the binarization process using the first threshold Th4, the influence of the counterfeit distribution F is eliminated by the first threshold Th4, and the second threshold is used 2 In the valuation process, it is assumed that the error could not be corrected due to the influence of the forged distribution F.

In the case of a two-dimensional code with forgery, code information different from each other may be acquired. The acquisition of code information that differs from each other means that the two-dimensional code includes a plurality of types of data, and an error correction code (Reed-Solomon code) corresponding to each of the plurality of types of data is included. The two-dimensional code is configured as an image including data representing code information and an error correction code for performing error correction of the data. Therefore, it is unlikely that a two-dimensional code containing a plurality of types of data and an error correction code corresponding to each of the plurality of types of data is accidentally generated, and it is presumed (determined) that the two-dimensional code was intentionally generated (forged). ) You can do it.

In step S320, the forgery determination unit 113 determines whether or not the code information acquired in the first code information acquisition process and the second code information acquisition process is different from each other. The forgery determination unit 113 determines that the two-dimensional code is forged when the code information is different from each other, proceeds to step S330, and when the code information matches each other, proceeds to the process. It is determined that the two-dimensional code is not forged, and the process proceeds to step S340.

In step S330, the counterfeiting response unit 114 executes a warning display process. In the warning display process, the counterfeiting response unit 114 indicates that the two-dimensional code may be forged together with the code information acquired in the first code information acquisition process and the second code information acquisition process. Display on 130. As a result, the image analysis device 100 can protect the user from being guided to a phishing site or the like.

In step S340, the forgery determination unit 113 executes the code information determination process. In the code information determination process, the forgery determination unit 113 should use the only code information that matches each other if the error correction is successful in both cases of the two-dimensional code QC in the stained state. To decide.

On the other hand, in the case of a two-dimensional code with forgery, if the error correction is successful, the only code information obtained by regarding it as a legitimate site is determined as the code information to be used. .. Forgery of a two-dimensional code is configured to lead to a phishing site or the like instead of a legitimate site with a probability of, for example, once in hundreds or thousands of times. Therefore, when a plurality of different thresholds are used, it is extremely unlikely that the error correction will succeed only in the direction intended by the forgery and will continue to fail until it times out.

In step S400, the image analysis unit 111 executes the code information utilization process. In the code information utilization process, the image analysis device 100 can request a connection to the website by using the acquired code information, for example, a URL (Uniform Resource Locator).

The imaging process (step S100) according to one embodiment is different from the imaging process (step S10) according to the comparative example in the following points. That is, in the imaging process (step S100) according to one embodiment, the LED light source 170 can emit light, and the two-dimensional code can be irradiated while changing the amount of light.

In order for the forgery to be configured to lead to a phishing site instead of a legitimate site with a very small probability, the reading environment of the 2D code, that is, the display state, ambient light, and imaging state of the 2D code (for example, It is presumed that the fluctuation of the imaging environment such as exposure and shutter speed is used. Therefore, if the two-dimensional code is displayed while changing the amount of light of the operation display unit 230, the forgery determination process (step S300) can detect the forgery with a higher probability.

In the present specification, "while changing" has a broad meaning, for example, not only when a two-dimensional code is displayed and imaged at each light amount of two or more stages, but also the light amount is continuously changed. It also includes automatic continuous shooting in the state of being allowed to shoot.

Further, "while changing the light" has a broad meaning and includes a change in the imaging environment including changing at least one of the amount of light and the spectrum. For counterfeiting, it is possible to change the amount of reflected light (in the case of printing) and the amount of emitted light (in the case of display) with almost no change in the brightness value of the Lab color space, which is difficult for the human eye to distinguish. is there.

In the above embodiment, it is assumed that the two-dimensional code QC is printed, but it can also be applied to the case where the two-dimensional code QC is displayed on the operation display unit 230 of the personal computer 200, for example. When the two-dimensional code QC is displayed on the operation display unit 230, the image analysis device 100 cooperates with the personal computer 200, and the image analysis unit 111 refers to the operation display unit 210 with respect to the control unit 210 of the personal computer 200. The two-dimensional code may be displayed while changing the amount of light of 230, and the two-dimensional code reading process according to one embodiment may be repeatedly executed.

In addition, since such forgery includes a plurality of types of data and error correction codes corresponding to the plurality of types of data, a peculiar peak is formed between the peak in the black region and the peak in the white region. It is also possible. Therefore, the image analysis unit 111 can also detect a peculiar peak by histogram analysis and determine the positional relationship (difference or distance of luminance gradation value) between the peculiar peak and the peak in the black region (or the peak in the white region). It may also be possible to presume counterfeiting and alert the user.

As described above, according to the image analysis system 10 according to the embodiment, it is possible to detect forgery of the code image and protect it from guidance to a phishing site or the like of the user. Further, the image analysis system 10 does not require any special hardware and can be easily implemented only by installing software.

C. Modification example:
The present invention can be implemented not only in the above embodiments but also in the following modifications.

Modification 1: In the above embodiment, it is assumed that the forged two-dimensional code contains two types of data and includes an error correction code corresponding to each of the two types of data. Not limited to type. The present invention can deal with a forged two-dimensional code including a plurality of types of data and an error correction code corresponding to each of the plurality of types of data.

Modification 2: In the above embodiment, the first binarization process using the first threshold value and the second binarization process using a second threshold value different from the first threshold value are included. Although the binarization process is executed three times, a plurality of binarization processes including three or more times may be executed.

Modification 3: In the above embodiment, a binarization process that automatically changes the threshold value by the mode method according to the imaging state of the code image is assumed, but the binarization process that uses the fixed threshold value is executed. The present invention is also applicable to an image forming apparatus. In such an image forming apparatus, when a peculiar peak is detected by histogram analysis, the amount of irradiation light or the amount of display light is changed so that the peculiar peak is arranged on both sides of a fixed threshold value, and a forgery determination process is performed. Can also be executed.

Modification 4: In the above embodiment, a smartphone is used as a mobile terminal, but the present invention can be applied to a mobile terminal such as a tablet if wireless communication is possible.

10 Image analysis system 100 Image analysis device (smartphone)
110, 210 Control unit 111 Image analysis unit 112 Error correction unit 113 Counterfeit judgment unit 114 Counterfeit response unit 160 Imaging unit 130, 230 Operation display unit 140, 240 Storage unit 150, 250 Communication interface unit 200 Personal computer

Claims (7)

An image reader that reads an image including a code image and generates image data,
An image analysis unit that acquires at least one code information by executing an analysis including error correction on the image data, and an image analysis unit.
When the at least one code information acquired based on the success of the error correction contains a plurality of mutually different code information, a forgery determination unit for determining that the code image is forged.
An image analysis device comprising. The image analysis apparatus according to claim 1.
The image analysis unit uses a first binarization process using the first threshold value and a second binary value using a second threshold value different from the first threshold value as an analysis including the error correction. An image analysis device that acquires at least one code information by executing a plurality of binarization processes including a conversion process. The image analysis apparatus according to claim 1 or 2, further
An image analysis device including an operation display unit that notifies the possibility of the forgery and displays a plurality of mutually different code information when it is determined that the code image is forged. The image analysis apparatus according to any one of claims 1 to 3, further comprising.
A light irradiation unit capable of irradiating the code image while changing the light is provided.
The image reading unit generates a plurality of image data in a state where the code image is irradiated while changing the light by the light irradiation unit.
The image analysis unit executes the analysis on each of the plurality of image data, and then performs the analysis.
The forgery determination unit is an image analysis device that determines whether or not the code image is forged for each of the plurality of image data. The image analysis apparatus according to any one of claims 1 to 4.
An image display device capable of displaying the code image while changing the light,
With
The image reading unit causes the image display device to display the code image while changing the light, reads the displayed code image, and generates a plurality of image data.
The image analysis unit executes the analysis on each of the plurality of image data, and then performs the analysis.
The forgery determination unit is an image analysis system that determines whether or not the code image is forged for each of the plurality of image data. An image reading process that reads an image including a code image and generates image data,
An image analysis step of acquiring at least one code information by executing an analysis including error correction on the image data, and
A forgery determination step of determining that the code image is forged when the at least one code information acquired based on the success of the error correction contains a plurality of mutually different code information.
An image analysis method comprising. An image analysis program for controlling an image analysis device.
An image reader that reads an image containing a code image and generates image data,
An image analysis unit that acquires at least one code information by executing an analysis including error correction on the image data, and a plurality of mutual at least one code information acquired based on the success of the error correction. An image analysis program for making the image analysis device function as a counterfeit determination unit that determines that the code image is counterfeited when the code information is different from the above.