Method and system for associating data features with data label protection

Abstract

The application discloses a kind of method and system for associating and protecting data features with data labels, and relates to the field of data security.The steps of the method include: data protection process: after sorting data features and / or data labels, grouping the sorted data features and / or data labels according to the preset grouping rules, and marking each group of data with a unique group identifier; according to the rotation rule corresponding to each group of data, rotate the data in each group, and change the association relationship of the data before rotation to the association relationship of the data after rotation.The application realizes the association protection of data features and data labels through simple data rotation adjustment, and compared with the existing technology which protects data features and data labels by using data encryption and decryption algorithm, the data rotation process of the application is very simple, the required calculation amount is very small, and it is very suitable for practical use and popularization.

Description

Technical Field

[0001] The present invention relates to the field of data security, and in particular to a method and system for associating and protecting data features with data tags. Background Art

[0002] After collecting data (images, text, point clouds, etc.), data labeling is required according to task requirements. Specifically, it refers to the process of processing the collected, unprocessed raw data or primary data, including voice, pictures, text, video and other types of data, and converting them into machine-recognizable information.

[0003] Common data annotation methods include:

[0004] (1) Rectangular box annotation: Rectangular box annotation is a simple processing method for object detection box annotation, which is often used to annotate people, vehicles, objects, etc. in autonomous driving.

[0005] (2) Polygonal annotation: Polygonal annotation refers to the use of polygonal boxes to mark irregular target objects in static images. Compared with rectangular box annotation, polygonal annotation can frame the target more accurately and is more targeted for irregular objects.

[0006] (3) Semantic segmentation: Semantic segmentation refers to dividing complex irregular images into regions based on the attributes of objects and labeling the corresponding attributes to help train image recognition models. It is often used in autonomous driving, human-computer interaction, virtual reality and other fields.

[0007] (4) Key point annotation: The biggest application of the key point annotation template is to mark the key points of the face. By marking key points in different directions, the functions of the characters in the image can be determined.

[0008] (5) 3D point cloud annotation: 3D point cloud annotation refers to the use of lidar data to perform frame selection and annotation for use in training artificial intelligence models such as computer vision and unmanned driving.

[0009] (6) 3D cube annotation: Different from point cloud annotation, 3D cube annotation is still based on the annotation of two-dimensional plane images. The annotator frames the edges of three-dimensional objects, obtains the vanishing point, and measures the relative distance between objects.

[0010] (7) Target tracking: Target tracking refers to the process of performing frame-by-frame annotation in dynamic images, marking the target objects in each frame and describing their motion trajectories. This type of annotation is often used to train autonomous driving models and video recognition models.

[0011] (8) Attribute discrimination: Attribute discrimination refers to identifying the target object in the image and labeling it with the corresponding attribute through manual or machine cooperation.

[0012] As can be seen, data annotation is expensive, especially when the amount of data is very large. The cost of creating data features and labeling each data feature is even higher. To prevent unauthorized parties from knowing data features and labels without compensation, data features and labels need to be protected.

[0013] Currently, data encryption and decryption algorithms are generally used to protect data features and data labels. Specific algorithms include:

[0014] (1) MD5 algorithm (Message-Digest Algorithm), a widely used cryptographic hash function, can generate a 128-bit (16-byte) hash value to ensure the integrity and consistency of information transmission.

[0015] (2) SHA-2 (Secure Hash Algorithm 2). A cryptographic hash function algorithm standard, one of the SHA algorithms, which can be further divided into six different algorithm standards, including: SHA-224, SHA-256, SHA-384, SHA-512, SHA-512 / 224, and SHA-512 / 256.

[0016] However, when the amount of data is very large, the computational complexity of the above encryption algorithm is very high, which is not convenient for people to use. Summary of the Invention

[0017] In response to the defects in the prior art, the technical problem solved by the present invention is: how to protect data features and corresponding data tags while significantly reducing the amount of calculation.

[0018] To achieve the above objectives, in a first aspect, embodiments of the present application provide a method for associating data features with data tags for protection, comprising the following steps:

[0019] Data protection process: After sorting the data features and / or data labels, the sorted data features and / or data labels are grouped according to the preset grouping rules, and each group of data is marked with a unique grouping identifier; according to the rotation rules corresponding to each group of data, the data in each group of data is rotated, and the association relationship of the data before the rotation is converted into the association relationship of the data after the rotation;

[0020] Data restoration process: Based on each group identifier and the corresponding rotation rule, restore the data features and / or data sorting of the corresponding group.

[0021] In conjunction with the first aspect, in one embodiment, the process of changing the association relationship of the pre-rotation data to the association relationship of the post-waiting data includes:

[0022] If only data features are rotated, the data feature A associated with a data label before the rotation will be changed to the data feature located at position A after the rotation; if only data labels are rotated, the data label A associated with a data feature before the rotation will be changed to the data label located at position A after the rotation; if both data features and data labels are rotated at the same time, the data features and data labels at the same position after the rotation will be associated.

[0023] In combination with the first aspect, in one embodiment, when data features or data tags are grouped, one of the data features and data tags is defined as an active rotation object, and the other is defined as a passive rotation object; the steps of the method include: sorting all active objects and grouping them according to the grouping rules, and marking a unique grouping identifier for each group of active rotation objects; according to the rotation rules of each group of active rotation objects, after rotating data for each group of active rotation objects, the initial active rotation object associated with each passive rotation object is modified to an active rotation object that is located at the position of the initial active rotation object after rotation.

[0024] In conjunction with the first aspect, in one embodiment, when grouping data features and data labels:

[0025] The process of sorting data features and / or data labels includes: sorting data features to form a data feature sequence, sorting data labels to form a data label sequence;

[0026] The grouping identifier includes a data feature grouping identifier corresponding to the data grouped by the data feature sequence, and a data label grouping identifier corresponding to the data grouped by the data label sequence;

[0027] The process of converting the association relationship of the data before rotation into the association relationship of the data after waiting includes: associating each data feature in the data feature sequence with the data tag at the same position in the data tag sequence;

[0028] The data restoration process includes: determining each group of data feature data and the corresponding rotation rules according to the data feature grouping identifier, and restoring the group of data features according to the rotation rules of each group of data features to form a correct data feature sequence; determining each group of data label data and the corresponding rotation rules according to the data tag grouping identifier, and restoring the group of data labels according to the rotation rules of each group of data tags to form a correct data label sequence; associating each data feature in the correct data feature sequence with the data label at the same position in the correct data label sequence.

[0029] In combination with the first aspect, in one embodiment, the rotation rules include the group data length for dividing each group of data into several rotation groups, and the rotation rules for each rotation group; the process of rotating the data in each group of data according to the rotation rules corresponding to each group of data includes: dividing each group of data into several rotation groups according to the specified length, and rotating the data in the rotation group according to the rotation rules of each rotation group; the group identifier includes the group data identifier corresponding to each group of data, and the rotation group identifier corresponding to each rotation group.

[0030] In combination with the first aspect, in one embodiment, the rotation rule of each rotation group is a unique rotation rule.

[0031] In combination with the first aspect, in one embodiment, the data restoration process includes: sending the group identifier to the authorized party, and when a data restoration request issued by the authorized party is received and the group identifier and identity information in the data restoration request are correct, restoring the association between the data features and the data tags through the rotation rules corresponding to the group identifier.

[0032] In combination with the first aspect, in one implementation, the grouping rule is to specify the data length of each group.

[0033] In a second aspect, an embodiment of the present application provides a system for associating and protecting data features with data tags, which is used to implement the method provided in the first aspect.

[0034] In a third aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method provided in the first aspect is implemented.

[0035] Compared with the prior art, the advantages of the present invention are:

[0036] The present invention adjusts the data sorting order of data features and / or data labels by specifying data rotation rules. Given that data features and data labels have a corresponding relationship, as long as the order of one of the data features and data labels is disordered, even if the other is sorted correctly, the corresponding relationship between the data features and data labels cannot be determined. Therefore, the present invention achieves the associated protection of data features and data labels through a simple data rotation adjustment method. Compared with the prior art that uses data addition and decomposition algorithms to protect data features and data labels, the data rotation process of the present invention is very simple, the required computational effort is very small, and it is very suitable for practical application and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 This is a flow chart of the first embodiment of the present invention;

[0039] Figure 2 This is a flow chart of the second embodiment of the present invention. DETAILED DESCRIPTION

[0040] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0041] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0042] The method for associating and protecting data features with data tags in an embodiment of the present invention includes the following steps: a data group rotation process: after sorting the data features and / or data tags that need to be protected, the sorted data features and / or data tags are grouped according to preset grouping rules, and each group of data is marked with a unique grouping identifier; according to the rotation rules corresponding to each group of data (i.e., the preset data sorting rules), the data in each group of data is rotated (i.e., the data arrangement order is adjusted), and the association relationship of the data before the rotation is changed to the association relationship of the data after the rotation.

[0043] Data restoration process: According to each group identifier and the corresponding rotation rule, after restoring the data features and / or data sorting of the corresponding group, the correct association between the data features and data labels can be obtained.

[0044] It can be seen from this that the present invention adjusts the data sorting order of data features and / or data labels by specifying data rotation rules, and changes the association between data features and data labels according to the sorting. In view of the fact that there is a corresponding relationship between data features and data labels, as long as the sorting of one of the data features and data labels is disordered, even if the sorting of the other is correct, the corresponding relationship between the data features and data labels cannot be known. Therefore, the present invention realizes the association protection of data features and data labels through a simple data rotation adjustment method. Compared with the prior art that uses data addition and solution algorithms to protect data features and data labels, the data rotation process of the present invention is very simple, the required amount of calculation is very small, and it is very suitable for practical application and promotion.

[0045] Preferably, in the above method, the process of changing the association relationship of the data before rotation into the association relationship of the data after waiting includes:

[0046] If only data features are rotated, feature A, which was previously associated with a data label, becomes the data feature at position A after the rotation. For example, if the data features are A, B, C, ..., X, Y, Z and are grouped by six data lengths, the data in the first group is ABCDEF, and the corresponding data labels are abcdef. In this case, the rotation rule can be set to 213213. Following the above swapping, the order is: ABCDEF corresponds to baedfc.

[0047] If only data labels are rotated, the data label A associated with a data feature before the rotation becomes the data label at position A after the rotation. Similar to the above example, when the data label rotation rule is 213213, abcdef corresponds to BAEDFC.

[0048] If data features and data labels are rotated at the same time, the data features and data labels at the same position after rotation are associated. Similar to the above example, when the rotation rule of the data labels is 213213 and the rotation rule of the data features is 231231, BAEDFC corresponds to bcafcd.

[0049] Preferably, when data features or data tags are grouped, the specific process of the above method includes: a data group rotation process: defining one of the data features and data tags as an active rotation object and the other as a passive rotation object. After sorting all active objects and grouping them according to the grouping rules, each group of active rotation objects is marked with a unique grouping identifier; according to the rotation rules of each group of active rotation objects, after data rotation is performed on each group of active rotation objects, the initial active rotation object associated with each passive rotation object is modified to an active rotation object that is located in the position of the initial active rotation object after the rotation.

[0050] Preferably, when grouping data features and data labels:

[0051] The above method includes sorting data features to form a data feature sequence, and sorting data labels to form a data label sequence.

[0052] The grouping identifiers in the above method include data feature grouping identifiers corresponding to the data grouped by the data feature sequence, and data label grouping identifiers corresponding to the data grouped by the data label sequence.

[0053] The process of converting the association relationship of the data before rotation into the association relationship of the data after waiting in the above method includes: associating each data feature in the data feature sequence with the data tag at the same position in the data tag sequence.

[0054] The data restoration process in the above method includes: determining each set of data feature data and the corresponding rotation rule based on the data feature group identifier, and restoring the set of data features based on the rotation rule of each set of data features to form a correct data feature sequence; determining each set of data label data and the corresponding rotation rule based on the data tag group identifier, and restoring the set of data labels based on the rotation rule of each set of data tags to form a correct data tag sequence. Each data feature in the data feature sequence is associated with the data tag at the same position in the data tag sequence.

[0055] It can be seen from this that after the present invention rotates the data features and data tags at the same time and resets the association relationship, the data features and data tags do not have any substantial association logic, which not only increases the difficulty of directly deciphering the data (it is necessary to decipher the rotation rules of the data features and data tags separately), but also enriches the types of "keys" (it is necessary to know the data feature grouping identifier, data feature rotation rules, data tag grouping identifier, and data tag rotation rules), increasing the difficulty for unauthorized parties to illegally obtain the key to restore the data.

[0056] Preferably, the grouping rule in the above method is to specify the data length of each group. The data lengths of different groups can be the same or different, and the specific length is determined according to the length of data to be protected.

[0057] Preferably, the rotation rule in the above method includes the length of the grouped data that divides each group of data into several rotation groups, and the rotation rule of each rotation group. On this basis:

[0058] (1) In the above method, the process of rotating the data in each group of data according to the rotation rule corresponding to each group of data includes: dividing each group of data into a number of rotation groups according to a specified length, and rotating the data in the rotation group according to the rotation rule of each rotation group.

[0059] (2) The group identifier in the above method includes the group data identifier corresponding to each group of data and the rotation group identifier corresponding to each rotation group.

[0060] From this, it can be seen that the present invention, on the basis of dividing data features and / or data labels into "large" groups, continues to perform specific rotations on the subdivided rotation groups, and then, while ensuring a reasonable range of computing resources, increases the difficulty of deciphering data through multiple data rotations, thereby improving the security of the data.

[0061] On this basis, the rotation rules of each rotation group are unique rotation rules, that is, the rotation rules of each rotation group are different, thereby further improving the security of the data.

[0062] Preferably, the above-mentioned data restoration process specifically includes: sending the group identifier to the authorized party, and when a data restoration request issued by the authorized party is received and the group identifier and identity information in the data restoration request are correct, restoring the association between data features and data tags through the rotation rules corresponding to the group identifier.

[0063] From this, it can be seen that the present invention only sends the group identifier to the authorized party, and the specific rotation rules for restoring data are stored in the background. On this basis, even if an unauthorized party illegally obtains the authorized party's information, the unauthorized party can only obtain the group identifier and cannot restore the data, which further improves the security of the data.

[0064] The method of the present invention is specifically described below through three embodiments.

[0065] Example 1

[0066] Example 1 rotates data features and data labels at the same time, see Figure 1 As shown, the specific process includes:

[0067] S101: sorting data features to form a data feature sequence, and sorting data labels to form a data label sequence.

[0068] S102: After grouping the data feature sequences and data label sequences according to different grouping rules (the grouping rules specify the data length of each group), each group of data features is marked with a data feature grouping identifier, and each group of data labels is marked with a data label grouping identifier.

[0069] S103: Rotate the data in each group of data according to the unique rotation rule corresponding to each group of data, specifically: divide each group of data into several rotation groups according to the specified length, and determine the rotation grouping identifier of each rotation group.

[0070] S104: Associating each data feature in the data feature sequence with the data tag at the same position in the data tag sequence.

[0071] S105: Send the group identifiers (data feature group identifier, data tag group identifier, and rotation group identifier) ​​to the authorized party. When a data restoration request is received from the authorized party and the group identifier and identity information in the data restoration request are correct, restore the association between the data features and data tags using the rotation rules corresponding to the group identifiers. The specific process includes:

[0072] Based on the data feature grouping identifier, determine the data feature data and the corresponding rotation rules for each group. Based on the rotation rules for each group of data features, restore the group of data features to form a correct data feature sequence. Based on the data label grouping identifier, determine the data label data and the corresponding rotation rules for each group of data labels. Based on the rotation rules for each group of data labels, restore the group of data labels to form a correct data label sequence. Associate each data feature in the data feature sequence with the data label at the same position in the data label sequence.

[0073] Example 2

[0074] Example 2 only rotates the data features, see Figure 2 As shown, the specific process includes:

[0075] S201: Sort the data features to form a data feature sequence.

[0076] S202: After grouping the data feature sequences according to the same grouping rule (the grouping rule specifies the data length of each group), each group of data features is marked with a data feature grouping identifier.

[0077] S203: Rotate the data in each group of data according to the non-unique rotation rule corresponding to each group of data (i.e., the rotation rules of different groups may be the same or different), specifically: divide each group of data into several rotation groups according to the same length, and determine the rotation group identifier of each rotation group.

[0078] S204: Modify the initial data feature associated with each data tag to a data feature located at the position of the initial data feature after rotation.

[0079] S205: Send the group identifier (data feature group identifier and rotation group identifier) ​​to the authorized party. When receiving a data restoration request from the authorized party and the group identifier and identity information in the data restoration request are correct, restore the association between the data features and data tags according to the rotation rule corresponding to the group identifier. The specific process includes:

[0080] Determine each group of data feature data and the corresponding rotation rules based on the data feature grouping identifier, and restore the group of data features according to the rotation rules of each group of data features to form a correct data feature sequence; modify the data feature A associated with each data tag to the data feature located at the position of data feature A after restoration.

[0081] Example 3

[0082] In the third embodiment, except that the rotation subject is the data tag, the rest of the process is the same as that of the second embodiment. After all the data tags and data features described in the second embodiment are exchanged, the content of the third embodiment is obtained.

[0083] The comparison of restoration difficulty and efficiency between Examples 1 to 3 is as follows:

[0084] Embodiment 1 rotates data features and data labels simultaneously, and has different grouping rules and unique rotation rules. Therefore, the difficulty of restoring the rotated data is very high. However, compared with embodiments 2 and 3 that only rotate data features or data labels, the calculation process of embodiment 1 is relatively complicated.

[0085] Therefore, the first embodiment is suitable for scenarios that attach great importance to data security, and the second and third embodiments are suitable for scenarios that take both data security and saving computing resources into consideration.

[0086] An embodiment of the present invention further provides a storage medium storing a computer program that, when executed by a processor, implements the above-described method. It should be noted that the storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a ROM (Read-Only Memory), a RAM (Random Access Memory), a magnetic disk, or an optical disk.

[0087] An embodiment of the present invention also provides a system for associating and protecting data features with data tags, including a memory and a processor, wherein the memory stores a computer program running on the processor, and the processor implements the above method when executing the computer program.

[0088] It will be understood by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable storage medium, which may include a computer-readable storage medium (or a non-transitory medium) and a communication medium (or a temporary medium).

[0089] As is well known to those skilled in the art, the term computer-readable storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically contains computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0090] For example, the computer-readable storage medium may be an internal storage unit of the electronic device of the aforementioned embodiment, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the electronic device.

[0091] The above are only specific implementations of the embodiments of the present invention, but the scope of protection of the embodiments of the present invention is not limited to them. Any person skilled in the art can easily conceive of various equivalent modifications or replacements within the technical scope disclosed in the embodiments of the present invention, and such modifications or replacements should be included in the scope of protection of the embodiments of the present invention. Therefore, the scope of protection of the embodiments of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for associating and protecting data features with data tags, characterized in that: The method comprises the following steps: Data protection process: After sorting the data features and / or data labels, the sorted data features and / or data labels are grouped according to the preset grouping rules, and each group of data is marked with a unique grouping identifier; according to the rotation rules corresponding to each group of data, the data in each group of data is rotated, and the association relationship of the data before the rotation is converted into the association relationship of the data after the rotation; Data restoration process: Determine each set of data feature data and the corresponding rotation rules based on the data feature grouping identifier, and restore the data features according to the rotation rules of each set of data features to form a correct data feature sequence; determine each set of data label data and the corresponding rotation rules based on the data label grouping identifier, and restore the data labels according to the rotation rules of each set of data labels to form a correct data label sequence; associate each data feature in the correct data feature sequence with the data label at the same position in the correct data label sequence; When grouping data features and data labels: The process of sorting the data features and / or data labels includes: sorting the data features to form a data feature sequence, sorting the data labels to form a data label sequence; The grouping identifier includes a data feature grouping identifier corresponding to the data grouped by the data feature sequence, and a data label grouping identifier corresponding to the data grouped by the data label sequence; The process of changing the association relationship of the data before rotation into the association relationship of the data after waiting includes: associating each data feature in the data feature sequence with the data tag at the same position in the data tag sequence.

2. The method for associating data features with data tags for protection according to claim 1, wherein: The process of converting the association relationship of the data before rotation into the association relationship of the data after waiting includes: If only data features are rotated, the data feature A associated with a data label before the rotation will be changed to the data feature located at position A after the rotation; if only data labels are rotated, the data label A associated with a data feature before the rotation will be changed to the data label located at position A after the rotation; if both data features and data labels are rotated at the same time, the data features and data labels at the same position after the rotation will be associated.

3. The method for associating data features with data tags for protection according to claim 1, wherein: When data features or data labels are grouped, one of the data features and data labels is defined as an active rotation object, and the other is defined as a passive rotation object; the steps of the method include: sorting all active objects and grouping them according to the grouping rules, marking each group of active rotation objects with a unique grouping identifier; according to the rotation rules of each group of active rotation objects, after rotating the data of each group of active rotation objects, the initial active rotation object associated with each passive rotation object is modified to an active rotation object that is located at the position of the initial active rotation object after the rotation.

4. The method for associating data features with data tags for protection according to claim 1, wherein: The rotation rules include the group data length for dividing each group of data into several rotation groups, and the rotation rules for each rotation group; the process of rotating the data in each group of data according to the rotation rules corresponding to each group of data includes: dividing each group of data into several rotation groups according to the specified length, and rotating the data in the rotation group according to the rotation rules of each rotation group; the group identifier includes the group data identifier corresponding to each group of data, and the rotation group identifier corresponding to each rotation group.

5. The method for associating data features with data tags for protection according to claim 4, wherein: The rotation rule of each rotation group is a unique rotation rule.

6. The method for associating and protecting data features with data tags according to any one of claims 1 to 5, characterized in that: The data restoration process includes: sending the group identifier to the authorized party, and when a data restoration request is received from the authorized party and the group identifier and identity information in the data restoration request are correct, restoring the association between data features and data tags through the rotation rules corresponding to the group identifier.

7. The method for associating and protecting data features with data tags according to any one of claims 1 to 5, characterized in that: The grouping rule specifies the data length of each group.

8. A system for associating data features with data tags for protection, characterized by: The system is used to implement the method described in any one of claims 1 to 7.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

Images