Image processing device, method executed on computer for controlling imaging, and program

Abstract

To provide a technique for supporting selection of an optical system parameter performed by an operator using an optical system.SOLUTION: An image processing device 100 constituting an image processing system 10 used by an operator includes: an optical system database 110 that stores imaging data obtained by imaging in the past using an optical system 140 constituting the image processing system 10; an approximate function creation unit 121 that defines a feature amount based on the imaging data as a function of an optical parameter based on the imaging data and the optical parameter; a search unit 122 that searches, using the function, for the optical parameter that yields better imaging results than the imaging data; and an optical system control unit 123 that controls the optical system 140 according to the searched out optical parameter to perform imaging.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a technique for capturing an image using an optical system, and more particularly to a technique for assisting in the selection of optical parameters for controlling the optical system. [Background technology]

[0002] In image inspection, in order to obtain images with a high S / N (Signal / Noise) ratio, the object is photographed multiple times while changing the position and angle of the optical system, such as the camera and lighting. At this time, image inspectors and other operators use past experience to predict what the image will look like after the change, and decide which optical system to try next, so adjusting the optical system requires a fair amount of experience.

[0003] Regarding optical systems, for example, Japanese Patent Application Laid-Open No. 2000-356569 (Patent Document 1) discloses "an analysis support device that can easily analyze the relationship between multiple types of physical property values that represent the characteristics of an optical system and the sensory quality of an image formed using that optical system." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2000-356569 Summary of the Invention [Problem to be solved by the invention]

[0005] According to the technology disclosed in Patent Document 1, it is possible to predict the correlation between multiple types of physical property values that represent the characteristics of an optical system and human judgment from past imaging results. However, it is not possible to specifically predict the results of imaging using an optical system. Therefore, there is a need for a technology that can predict the results of imaging using an optical system.

[0006] The present disclosure has been made in view of the above-described background, and an object according to one aspect is to provide a technique for assisting in the selection of parameters of an optical system. [Means for solving the problem]

[0007] According to one embodiment, there is provided an image processing device including: a database storing imaging data obtained in past imaging using an optical system; an approximation function creation unit that defines a feature quantity based on the imaging data as a function of the optical parameters based on the imaging data and optical parameters; a search unit that uses the function to search for optical parameters that will produce better imaging results than those obtained using the imaging data; and an optical system control unit that causes the optical system to perform imaging in accordance with the searched optical parameters.

[0008] According to another embodiment, there is provided a computer-implemented method for controlling photography, the method including the steps of: accessing a database storing photography data obtained in past photography using an optical system; defining a feature quantity based on the photography data as a function of the optical parameters based on the photography data and optical parameters; using the function to search for optical parameters that produce better photography results than those obtained using the photography data; and causing the optical system to perform photography in accordance with the searched optical parameters.

[0009] According to yet another embodiment, there is provided a program for causing a computer to execute any of the methods described above.

[0010] According to one embodiment, a technique is provided to assist in the selection of parameters of an optical system.

[0011] The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating a configuration of an image processing system 10. [Figure 2] FIG. 1 is a block diagram showing the hardware configuration of a computer device 200 that implements an image processing device 100. [Figure 3] 1 is a flowchart (part 1) showing a part of the processing executed by a CPU 1 of a computer device 200 operating as an image processing device 100. [Figure 4] 10 is a flowchart (part 2) showing a part of the processing executed by the CPU 1 of the computer device 200 operating as the image processing device 100. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. The names and functions of the components are also the same. Therefore, detailed description thereof will not be repeated.

[0014] Embodiment 1 The configuration of image processing system 10 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of image processing system 10. Image processing system 10 includes image processing device 100 and optical system 140. In one aspect, image processing system 10 is used by an operator who inspects screws, circuit boards, and other processed or assembled products.

[0015] The image processing device 100 includes an optical system database 110, a selection unit 120, an approximate function creation unit 121, a search unit 122, an optical system control unit 123, an image processing unit , and an image display unit .

[0016] The optical system 140 mainly comprises a camera 141, an illumination device 142, a stage 143, and an actuator 144. The light source of the illumination device 142 is not particularly limited, and an LED (Light Emitting Diode), a halogen bulb, or the like may be used. The type of illumination device 142 may be, for example, transmitted illumination or coaxial illumination, but other forms of illumination may also be used.

[0017] The number of cameras 141, lighting 142, stages 143, and actuators 144 is not limited to one, and may be multiple. For example, in one aspect, when stage 143 moves in one axial direction, one camera 141, one lighting 142, and one actuator 144 may constitute optical system 140. In another aspect, when stage 143 moves in two axial directions, one or more cameras 141, one lighting 142, and one actuator 144 may constitute optical system 140 for each axis.

[0018] The optical system database 110 stores images of past photographed results, values of optical parameters at the time of the photographing, and values of feature amounts. Here, the optical parameters include, for example, the angle of the camera 141, the angle of the lighting 142, and the brightness of the lighting 142. The angle of the camera 141 is, for example, the angle between the photographing direction and the vertical direction, or the angle between the photographing direction and the horizontal direction. The feature amounts are values used to determine the quality of the image, such as the contrast of the inspection location and the area occupied by a foreign object in the image of the inspection target.

[0019] The selection unit 120 selects from the optical system database 110 an image, optical parameter values, and feature values for each of one or more objects that resemble the object to be photographed, and outputs the selected image, optical parameter values, and feature values to the approximation function creation unit 121.

[0020] The approximation function creation unit 121 creates a function (also referred to as an approximation function) that defines the relationship between the feature amount selected by the selection unit 120 and the optical parameter value, and outputs the created approximation function to the search unit 122. The approximation function is expressed as, for example, a quadratic function, a Gaussian function, or the like.

[0021] The search unit 122 searches for good optical parameters based on the approximation function created by the approximation function creation unit 121, and sequentially outputs the found good optical parameters to the optical system control unit 123. In this embodiment, a good optical parameter is, for example, a parameter whose value of the approximation function (i.e., the value of the feature amount) brings about a desirable result, for example, an optical parameter whose value of the approximation function is equal to or greater than a preset threshold value (for example, S / N ratio).

[0022] The optical system control unit 123 controls the optical system 140 based on the input optical parameter values. The objects of control include the angle of the camera 141, the angle or brightness of the lighting 142, the inclination of the stage 143 relative to the horizontal direction, the position of the actuator 144, and the like.

[0023] The optical system 140 photographs an object and outputs an image including the object under the control of the optical system control unit 123. The output image is input to the image processing unit .

[0024] The image processing unit 124 performs image processing on the input image and calculates a feature amount using the processed data. The calculated feature amount is the contrast or area, etc.

[0025] The image display unit 130 displays the image input from the image processing unit 124 .

[0026] In one aspect, the optical system database 110 is realized by a hard disk or other nonvolatile storage device included in a computer device. The selection unit 120, the approximate function creation unit 121, the search unit 122, the optical system control unit 123, and the image processing unit 124 are realized by a CPU (Central Processing Unit) or other processor included in the computer executing software. The image display unit 130 is realized as a monitor device included in the computer or an external monitor device connected to the computer device.

[0027] A specific configuration of image processing device 100 according to the present embodiment will now be described with reference to Fig. 2. Fig. 2 is a block diagram showing the hardware configuration of a computer device 200 that realizes image processing device 100.

[0028] The computer device 200 mainly includes the following components: a CPU 1 that executes programs; a mouse 2 and keyboard 3 that receive instructions input by the user of the computer device 200; a RAM 4 that volatilely stores data generated by the CPU 1 executing the programs or data input via the mouse 2 or keyboard 3; a hard disk 5 that nonvolatilely stores data; an optical disk drive 6; a communication interface (I / F) 7; and a monitor 8. The components are interconnected by a data bus. A CD-ROM (Compact Disc - Read Only Memory) 9 or other optical disk is inserted into the optical disk drive 6.

[0029] The processing in the computer device 200 is realized by software executed by each piece of hardware and the CPU 1. Such software may be pre-stored on the hard disk 5. Alternatively, the software may be stored on a CD-ROM 9 or other recording medium and distributed as a computer program. Alternatively, the software may be provided as a downloadable application program by an information provider connected to the Internet. Such software is read from the recording medium by an optical disk drive 6 or other reading device, or downloaded via the communication interface 7, and then temporarily stored on the hard disk 5. The software is read from the hard disk 5 by the CPU 1 and stored in the RAM 4 in the form of an executable program. The CPU 1 executes the program.

[0030] Each component constituting the computer device 200 shown in FIG. 2 is a general component. Therefore, one essential part of the technical idea disclosed in this specification can be said to be software stored in the RAM 4, hard disk 5, CD-ROM 9, or other recording medium, or software downloadable via a network. The recording medium may include a non-transitory computer-readable data recording medium. Note that the operation of each piece of hardware in the computer device 200 is well known, so detailed description will not be repeated.

[0031] The recording medium is not limited to a CD-ROM, a FD (Flexible Disk), or a hard disk, but may also be a medium that carries a program in a fixed manner, such as an SSD (Solid State Drive), a magnetic tape, an optical disk (MO (Magnetic Optical Disc) / MD (Mini Disc) / DVD (Digital Versatile Disc)), an IC (Integrated Circuit) card (including a memory card), an optical card, a mask ROM, an EPROM (Electronically Programmable Read-Only Memory), an EEPROM (Electronically Erasable Programmable Read-Only Memory), or a semiconductor memory such as a flash ROM.

[0032] The program referred to here includes not only a program that can be directly executed by a CPU, but also a source program, a compressed program, an encrypted program, and the like.

[0033] The control structure of the image processing device 100 will be described with reference to Figures 3 and 4. Figures 3 and 4 are flowcharts showing part of the processing executed by the CPU 1 of the computer device 200 operating as the image processing device 100. The following description will be given of a case where the degree of looseness of a screw fastened to an object is inspected. In the following example, the optical system 140 has one camera 141 and one light 142. The optical parameters include the angle θ of the camera 141.

[0034] In step S310, the CPU 1 controls the selection unit 120 to select data, i.e., optical parameters and feature quantities, of an object similar to the inspection object to be photographed this time from the optical system database 110. In one aspect, the selection unit 120 may select the optical parameters and feature quantities by having a user of the image processing device 100 (e.g., an inspection staff member) select one of the data displayed on the monitor 8. In another aspect, if the selection unit 120 has an AI (artificial intelligence) module, the selection unit 120 may use the AI to calculate the similarity between the object data and past data and select optical parameters and feature quantities with a high similarity (small difference between the data). In this case, a high similarity means that the calculated similarity is greater than a threshold set by the user. A small difference between the data means that the difference is smaller than a threshold set by the user. Note that the similarity is calculated using a known method. Therefore, the details of the similarity calculation method will not be repeated. The selected optical parameters and feature quantities are input to the approximation function creation unit 121.

[0035] In step S320, CPU 1, as approximation function creation unit 121, uses the selected optical parameters and feature amounts to create a function (approximation function) that defines the relationship between the feature amounts based on the imaging data and the optical parameters. As an example, a case will be described in which the relationship between the optical parameter (θ) and the feature amount (f(θ)) based on the imaging data using the optical parameter is approximated by a quadratic function expressed by the following equation (1). Here, A, B, and C are coefficients. f(θ)=Aθ 2 +Bθ+C (1) For example, in one aspect, if one optical parameter is selected in step S310, CPU 1 determines coefficients A, B, and C using the least squares method. In another aspect, if multiple optical parameters are selected in step S310, CPU 1 creates a function for each optical parameter. Then, CPU 1 creates an approximate function f(θ) taking into account the similarity between the object data and past data. For example, CPU 1 selects two optical parameters and derives two approximate functions f1(θ) and f2(θ) from the first optical parameter and the second optical parameter using the least squares method (see equations (2) and (3)). Here, A1, A2, B1, B2, C1, and C2 are coefficients. f1(θ)=A1θ 2 +B1θ+C1(2) f2(θ)=A2θ 2 +B2θ+C2(3) As an example, suppose that the similarity of an image based on the first optical parameter is 70% and the similarity of an image based on the second optical parameter is 30%. The approximate function f(θ) created in this case is expressed as in equation (4). f(θ)=(0.7A1+0.3A2)θ 2 +(0.7B1+0.3B2)θ+0.7C1+0.3C2(4) By using multiple pieces of data stored in the optical system database 110 in this manner, the image processing device 100 according to this embodiment can create accurate approximation functions even for objects that are not included in the optical system database 110.

[0036] The coefficients A, B, and C of the optical parameter approximation function f(θ) are generally determined by the material or shape, feature quantities, etc. of the object. As an example, assume that the optical system database 110 stores data on screws attached to metal and data on connectors attached to plastic. In such a case, there may be a need to newly adjust the optical system 140 that inspects screws attached to plastic. In this case, the image processing device 100 selects corresponding data from the optical system database 110 using the material (plastic) of the object as a key and adjusts the optical system 140 using the selected data. The image processing device 100 can more efficiently adjust the optical system by using the data on the connector attached to plastic, rather than using the above-mentioned approximation function derived by combining two sets of data, namely, the data on screws attached to metal and the data on the connector attached to plastic.

[0037] In step S330, the CPU 1 functions as the search unit 122 to search for good optical parameters using the approximation function created in step S320.

[0038] 4, in step S410, the CPU 1 places the initial optical parameters on the approximation function. There are no particular limitations on how the initial optical parameters are determined. As an example, the CPU 1 divides the range between the upper limit and lower limit of the possible values into equal intervals set in advance, and sets each value as an initial optical parameter.

[0039] In step S420, the CPU 1 calculates the gradient ∇f for each initial optical parameter. Here, the gradient ∇f is a vector whose components are the derivatives of each component of the approximate function f(θ). For example, the gradient ∇f(θ1) at a point θ=θ1 is expressed by equation (5). ∇f(θ1)=(2Aθ1+B) (5) In step S430, the CPU 1 determines the next optical parameter to be searched. More specifically, the CPU 1 changes the optical parameter in the direction in which the gradient found in S420 increases, and sets the changed optical parameter as the next optical parameter to be searched. An optical system with a high contrast between the screw and its surroundings is considered to be a better optical system than an optical system with a low contrast. Therefore, by searching for optical parameters in the direction in which the gradient increases, the CPU 1 is more likely to be able to find better optical parameters. The CPU 1 can determine the optical parameter to be added by taking the midpoint between the value of the parameter adjacent to the initial optical parameter. More specifically, if the original optical parameter is θ=θ1 and the parameter adjacent in the direction in which the gradient increases is θ=θ2, the next optical parameter θ3 to be searched is determined as shown in equation (6). θ3=(θ1+θ2) / 2 (6) In another aspect, the CPU 1 can determine the optical parameters by taking the weights into consideration. If the weights are W1 and W2, the CPU 1 can determine the optical parameters as shown in Equation (7). θ3=(W1θ1+W2θ2) / (W1+W2) (7) By gradually searching for an approximate function using a gradient in this way, any type of approximate function can be used, and when there is a large deviation between the approximate function and the true function, the optical parameters can be searched for while correcting the deviation.

[0040] In step S440, CPU 1 calculates the degree of clustering of the optical parameters to be searched next. First, CPU 1 classifies the optical parameters using the k-means method, an example of a clustering (classification) method. Note that this method is not limited to the k-means method. Next, for the cluster into which the largest number of optical parameters are classified, CPU 1 calculates the distance between the value of each optical parameter included in the cluster and the center of gravity of the cluster, and calculates the average value. By searching for optical parameters based on the degree of clustering of the optical parameters in this way, CPU 1 can find optical parameters that are less susceptible to ambient light and variations in the object. Here, ambient light refers to lighting other than that from optical system 140, such as fluorescent lights or light entering through a window.

[0041] For example, a common search method is to simply search for optical parameters that maximize the value of the approximation function and determine the optical parameters as good optical parameters. According to this method, if the approximation function has a steep maximum value on a spike, the steep maximum value can be determined to be a good optical parameter. However, a steep slope around the maximum value means that the feature value will significantly decrease when the optical conditions change slightly due to ambient light or object variations. As a result, an image captured by the optical system 140 to which the optical parameters are applied will be inappropriate. On the other hand, according to the image processing device 100 of this embodiment, initial optical parameters are assigned and better optical parameters are searched for based on the concentration of optical parameters. In this case, the maximum value where the most parameters are concentrated has a wide base, allowing the image processing device 100 to find optical system parameters that are less affected by ambient light or object variations.

[0042] In step S450, CPU 1 determines whether the average value calculated in step S440 is equal to or greater than a preset specified value. If CPU 1 determines that the average value is equal to or greater than the specified value (YES in step S450), CPU 1 switches control to step S460. If not (NO in step S450), CPU 1 returns control to step S420.

[0043] In step S460, the CPU 1 outputs the optical parameters obtained as a result of the search to the optical system control unit 123. After that, the CPU 1 returns control to the main flow.

[0044] Referring again to FIG. 3, in step S340, CPU 1, as optical system control unit 123, controls optical system 140 based on the optical parameters searched for by search unit 122. For example, if the optical parameter is the angle of illumination 142, CPU 1 changes the angle of illumination 142 of optical system 140. CPU 1 takes a photograph of the object using camera 141 of optical system 140. The image obtained by the photographing is input from camera 141 to image processing unit 124. Note that the method of selecting the optical parameters is not particularly limited. As an example, CPU 1 sequentially selects all optical parameters included in the optical parameters input from search unit 122 to optical system control unit 123, and photographs the object using each selected optical parameter.

[0045] In step S350, CPU 1 performs image processing as image processing unit 124 and calculates the contrast between the screw and its surroundings as a feature amount. The image processing algorithm is not particularly limited, and various algorithms can be applied. Furthermore, the feature amount is not limited to the contrast between the screw and its surroundings, and CPU 1 may calculate one or more feature amounts. A feature amount other than the contrast may be, for example, the area of a foreign object found in the captured area, such as a scratch or dent formed on the surface of a component.

[0046] In step S360, CPU 1 determines whether to continue processing. More specifically, if the feature amount calculated in step S350 is equal to or greater than a predetermined reference value, or if the number of searches for the optical parameters is equal to or greater than a predetermined specified number of times (YES in step S360), CPU 1 stores the image resulting from the shooting, the values of the optical parameters at the time of shooting, and the calculated feature amount values in optical system database 110, and displays the shot image on image display unit 130. Otherwise (NO in step S360), CPU 1 returns control to step S320 and continues creating the approximation function.

[0047] As described above, the image processing device 100 according to the first embodiment selects, from the optical system database 110, images, optical parameter values, and feature amounts for each of one or more objects similar to the object to be photographed, and creates an approximation function using the parameter values and feature amounts as explanatory variables. This allows the image processing device 100 to narrow down candidates for the setting conditions (parameter values) of the optical system before photographing the object, and therefore the image processing device 100 can efficiently and automatically adjust the optical system 140. This also reduces variations in the adjustment time for the optical system 140 depending on the experience of the user (e.g., an inspector), and derives appropriate photographing conditions without relying on the user's experience.

[0048] Furthermore, the image processing device 100 calculates feature amounts from the captured image using the image processing unit 124, and stores the feature amounts, the capturing conditions, and the captured image in the optical system database 110. This allows the image processing device 100 to accumulate the capturing conditions and feature amounts, thereby enabling it to create a more accurate approximation function. As a result, more desirable capturing conditions can be more easily derived.

[0049] Variant. In other aspects, there may be cases where a plurality of feature quantities are taken into consideration in selecting optical parameters, and therefore, a case where a plurality of feature quantities are taken into consideration will be described.

[0050] For example, when two feature quantities are taken into consideration in determining the quality of a captured image, the optical parameters obtained as a result of searching for the first feature quantity may differ from the optical parameters obtained as a result of searching for the second feature quantity. Since only one optical parameter is used to capture one image, in this case, the optical system 140 needs to capture two images, which increases the number of steps required for the capture.

[0051] To avoid such problems, in step S360, the image processing device 100 according to this modification outputs not only the best optical parameter value but also all optical parameter values whose feature values exceed a preset reference value. At this time, if there is an optical parameter that overlaps between the optical parameter output when searching for the first feature value and the optical parameter output when searching for the second feature value, the CPU 1 stores the overlapping optical parameter in the optical system database 110. If there is no overlapping optical parameter, the CPU 1 can find the overlapping optical parameter by successively decreasing the reference value.

[0052] As described above, the image processing device 100 according to this embodiment and the modified examples creates an approximation function, and then uses the created approximation function to narrow down candidates for the optical parameters of the optical system 140 before capturing an image, and present the candidate optical parameters. This allows the user of the image processing device 100 to narrow down candidates for the optical parameters without relying on experience, and thus allows efficient adjustment of the optical system 140. Stable capturing is possible regardless of the user's level of experience.

[0053] The image processing device 100 stores image data (feature amounts) obtained as a result of shooting using optical parameters determined by the created approximation function and the values of the optical parameters in the optical system database 110. By storing the optical parameter values and feature amounts, the image processing device 100 can more easily derive approximation functions with improved accuracy. This allows the current adjustment result of the optical system 140 to be used in the next adjustment.

[0054] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0055] 1 CPU, 2 mouse, 3 keyboard, 4 RAM, 5 hard disk, 6 optical disk drive, 7 communication interface, 8 monitor, 9 CD-ROM, 10 image processing system, 100 image processing device, 110 optical system database, 120 selection unit, 121 approximation function creation unit, 122 search unit, 123 optical system control unit, 124 image processing unit, 130 image display unit, 140 optical system, 141 camera, 142 lighting, 143 stage, 144 actuator, 200 computer device.

Claims

1. a database storing photographic data obtained in past photographs using an optical system; an approximation function creation unit that defines a feature quantity based on the imaging data as a function of the optical parameters based on the imaging data and optical parameters; a search unit that uses the function to search for optical parameters that will result in a better photographing result than the photographing data; and an optical system control unit that causes the optical system to take an image in accordance with the searched optical parameters.

2. The image processing device according to claim 1 , wherein the photographing data includes image data obtained by the previous photographing, values of optical parameters used in the previous photographing, and feature amounts calculated from the image data.

3. The image processing device according to claim 2 , wherein the approximation function creating unit creates one or more approximation functions using past values of the optical parameters and the feature amounts.

4. 4. The image processing device according to claim 1, wherein the search unit searches for optical parameters that will bring about good photographing results by searching for optical parameters in a direction in which the gradient of the function increases.

5. 4. The image processing device according to claim 1, further comprising an image processing unit for calculating a feature amount from an image obtained by photographing.

6. Locating the optical parameters includes: equally dividing an interval between an upper limit value and a lower limit value that the optical parameter can take at a predetermined interval to generate a plurality of initial optical parameter values; determining a gradient of the function at each value of the plurality of initial optical parameters; 4. The image processing apparatus according to claim 1, further comprising: changing the initial optical parameters in a direction in which the gradient increases.

7. 1. A computer-implemented method for controlling photography, comprising: accessing a database storing photographic data obtained in past photographs taken using an optical system; defining a feature quantity based on the imaging data as a function of the optical parameters based on the imaging data and the optical parameters; using the function to search for optical parameters that will produce better imaging results than the imaging data; and causing the optical system to take an image in accordance with the searched optical parameters.

8. The method according to claim 7 , wherein the photographing data includes image data obtained by the previous photographing, values of optical parameters used in the previous photographing, and feature amounts calculated from the image data.

9. The method according to claim 8 , wherein the defining step includes creating one or more approximation functions using past values of the optical parameters and the feature quantities.

10. The method according to claim 7 , wherein the searching step includes searching for optical parameters that bring about the good photographing result by searching for optical parameters in a direction in which the gradient of the function increases.

11. The method according to claim 7 , further comprising the step of calculating a feature amount from the image obtained by photographing.

12. The step of searching for optical parameters includes: a step of equally dividing an interval between an upper limit value and a lower limit value that the optical parameter can take at a predetermined interval to generate a plurality of initial optical parameter values; determining a gradient of the function at each value of the plurality of initial optical parameters; The method according to claim 7 or 8, further comprising the step of changing the initial optical parameters in a direction in which the gradient increases.

13. A program that causes a computer to execute the method according to any one of claims 7 to 11.

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