JP6881986B2 - Data compression device, data decompression device, control method, program and storage medium - Google Patents

Description

The present invention relates to a technique for compressing or decompressing data.

Conventionally, a technique for efficiently processing or storing a large amount of measurement data has been known. For example, Patent Document 1 discloses a technique for shortening the processing time of three-dimensional CG display of point cloud data output by a laser scanner mounted on a moving body. Further, Patent Document 2 discloses a technique for compressing three-dimensional data.

Japanese Unexamined Patent Publication No. 2015-158772 Japanese Unexamined Patent Publication No. 2016-115332

When saving the output of a measuring device such as a laser scanner mounted on a moving body, the amount of data becomes enormous, so it is preferable to compress and save the data. In addition, since the types of features existing around the road are generally limited, it is convenient to be able to efficiently compress the data of features existing frequently around the road.

The present invention has been made, for example, in order to solve the above-mentioned problems, and an object of the present invention is to provide a data compression device capable of suitably compressing measurement data.

The invention according to claim 1 is a data compression device, in which a storage unit that stores a template representing the outer shape of a feature, an acquisition unit that acquires measurement data output by the measurement device, and the measurement data are compressed. The compression unit includes a compression unit that generates compressed data, and the compression unit compresses parameters for approximating the measurement data with a template representing the outer shape of the feature with respect to the measurement data corresponding to the feature. It is characterized by being generated as data.

The invention according to claim 7 is a control method executed by a data compression device having a storage unit that stores a template representing the outer shape of a feature, and includes an acquisition step of acquiring measurement data output by the measurement device, and the above-mentioned. It has a compression step of generating compressed data obtained by compressing the measurement data, and the compression step approximates the measurement data to the measurement data corresponding to the feature by a template representing the outer shape of the feature. The parameter of is generated as the compressed data.

The invention according to claim 8 is a program executed by a computer that refers to a storage unit that stores a template representing the outer shape of a feature, and includes an acquisition unit that acquires measurement data output by a measurement device, and the measurement data. The computer is made to function as a compression unit for generating compressed data, and the compression unit is used to approximate the measurement data to the measurement data corresponding to the feature by a template representing the outer shape of the feature. The parameter is generated as the compressed data.

This is a schematic configuration of a data compression system. The block configuration of the in-vehicle device is shown. An example of the data structure of the feature dictionary data and the parameter determination DB is shown. It is a flowchart of a compression process. It is a flowchart of a decompression process. The outline of the data compression system according to the modification is shown. The outline of the data compression system according to the modification is shown.

According to a preferred embodiment of the present invention, the data compression device compresses the storage unit that stores the template representing the outer shape of the feature, the acquisition unit that acquires the measurement data output by the measurement device, and the measurement data. The compression unit includes a compression unit that generates compressed data, and the compression unit compresses parameters for approximating the measurement data with a template representing the outer shape of the feature with respect to the measurement data corresponding to the feature. Generate as data.

The data compression device includes a storage unit, an acquisition unit, and a compression unit. The storage unit stores a template representing the outer shape of the feature. Here, "feature" refers to all objects on the ground regardless of whether they are natural or artificial, and includes flat objects such as white lines painted on the road. A "template" is data representing a typical outer shape (appearance) of a target feature. The acquisition unit acquires the measurement data output by the measuring device. The compression unit generates compressed data obtained by compressing the measurement data. Here, the compression unit generates, as compressed data, parameters for approximating the measurement data with the above-mentioned template with respect to the measurement data corresponding to the feature in which the template is stored in the storage unit. According to this aspect, the data compression device can suitably compress the measurement data by expressing the measurement data of the feature in which the template is stored by the parameters for approximating the template. In this case, the compressed feature measurement data can be approximately restored based on the template and parameters.

In one aspect of the data compression device, the compression unit generates at least a parameter representing the position of the feature measured by the measuring device and a parameter for adjusting the size of the template as the parameters. In this aspect, the data compression device is more suitable for the measurement data of the feature by the template and the parameter corresponding to the feature even when a specific kind of feature of various sizes exists at various positions. Can be compressed.

In another aspect of the data compression device, the storage unit stores setting information that defines parameters to be generated for each template, and the compression unit corresponds to the feature based on the setting information. Determine the parameters to be generated for the measurement data to be generated. According to this aspect, the data compression device can easily grasp the parameter to be determined by referring to the setting information.

In another aspect of the data compression device, the data compression device divides the measurement data acquired by the acquisition unit into each feature, and provides a corresponding template for each measurement data divided by the division unit. It further includes a specific part to be specified. According to this aspect, the data compression device can suitably specify the template corresponding to the measurement data acquired by the acquisition unit.

In another aspect of the data compression device, the measuring device moves with the moving body to generate measurement data of features existing around the moving body. In general, since the types of features existing around roads and the like on which moving objects move are limited, it is possible to store templates of features existing around roads and the like in advance. Therefore, according to this aspect, the data compression device can appropriately compress the measurement data of the features existing around the moving body by parameterizing them using a template.

According to another preferred embodiment of the present invention, the data decompression device includes a storage unit that stores a parameter generated by the data compression device according to any one of the above and a template corresponding to the parameter, and the storage unit. A decompression unit that generates approximate data of measurement data based on the stored combination is provided. According to this aspect, the data decompression device can suitably generate approximate data of the measurement data before compression based on the parameters generated by the data compression device.

According to another preferred embodiment of the present invention, the control method is executed by a data compression device having a storage unit that stores a template representing the outer shape of the feature, and the measurement data output by the measurement device is acquired. It has a step and a compression step of generating compressed data obtained by compressing the measurement data, and the compression step is a template for representing the measurement data of the feature with respect to the measurement data corresponding to the feature. The parameters for closer approximation are generated as the compressed data. By executing this control method, the data compression device can suitably compress the measurement data of the feature in which the template is stored.

According to another preferred embodiment of the present invention, a program executed by a computer that refers to a storage unit that stores a template representing the outer shape of a feature, and an acquisition unit that acquires measurement data output by the measurement device. The computer is made to function as a compression unit that generates compressed data obtained by compressing the measurement data, and the compression unit uses a template that represents the outer shape of the feature with respect to the measurement data corresponding to the feature. Parameters for approximation are generated as the compressed data. By executing this program, the data compression device can suitably compress the measurement data of the feature in which the template is stored. Preferably, the program is stored in a storage medium.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[Overview of data compression system]
FIG. 1 is a schematic configuration of a data compression system according to this embodiment. The data compression system includes a vehicle traveling on the road and an in-vehicle device 1 moving together with the vehicle.

The vehicle-mounted device 1 has a lidar (Light Detection and Ranking) 30 installed in the vehicle. Then, the vehicle-mounted device 1 compresses and stores the point cloud data related to the features around the vehicle (including the sign 50 in FIG. 1) output by the rider 30. The in-vehicle device 1 is an example of the "data compression device" in the present invention.

The rider 30 measures the distance to an object existing in the outside world discretely by emitting a pulsed laser with respect to a predetermined angle range in the horizontal direction and the vertical direction, and a three-dimensional point indicating the position of the object. Generate groups data. In this case, the rider 30 has an exit unit that emits a pulsed laser while changing the irradiation direction, a light receiving unit that receives reflected light (scattered light) of the irradiated pulse laser, and a point group based on a light receiving signal output by the light receiving unit. It has an output unit that outputs data. The point cloud data is generated based on the irradiation direction corresponding to the pulsed laser received by the light receiving unit and the response delay time of the pulsed laser specified based on the above-mentioned received signal. The rider 30 is an example of the “measurement device” in the present invention, and the point cloud data is an example of the “measurement data” in the present invention. Instead of scanning in both the horizontal direction and the vertical direction, the rider 30 may incline the emission direction of the pulse laser from the horizontal direction so that the scanning surface is oblique to the horizontal direction.

FIG. 2 is a block diagram showing a functional configuration of the vehicle-mounted device 1. The on-board unit 1 mainly includes a communication unit 11, a storage unit 12, a sensor unit 13, an input unit 14, a control unit 15, and an output unit 16. Each of these elements is connected to each other via a bus line.

The communication unit 11 performs data communication with another device based on the control of the control unit 15. The storage unit 12 stores a program executed by the control unit 15 and information necessary for the control unit 15 to execute a predetermined process. Further, the storage unit 12 stores the feature dictionary data 20 referred to during the compression process and the compressed data 21 which is the data after the point cloud data is compressed. The feature dictionary data 20 includes data (also referred to as a “template”) that typically represents the outer shape of each feature, as will be described later. In addition, the storage unit 12 may further store map data used for route guidance or automatic driving.

The sensor unit 13 is composed of an internal sensor for detecting the state of the vehicle and an external sensor for recognizing the surrounding environment of the vehicle. In addition to the rider 30 described above, the sensor unit 13 includes a camera 31 for photographing the scenery outside the vehicle and a GPS receiver. 32, a gyro sensor 33, a speed sensor 34, and the like are included. The outputs of the GPS receiver 32, the gyro sensor 33, the speed sensor 34, and the like are used to identify, for example, the current position and traveling direction of the vehicle.

The input unit 14 is a button, a touch panel, a remote controller, a voice input device, etc. for the user to operate, and the output unit 16 is, for example, a display, a speaker, or the like that outputs under the control of the control unit 15.

The control unit 15 includes a CPU that executes a program and the like, and controls the entire vehicle-mounted device 1. In this embodiment, the control unit 15 compresses the point cloud data output by the rider 30 with reference to the feature dictionary data 20, and stores the point cloud data as the compressed data 21 in the storage unit 12. Further, the control unit 15 performs route guidance and / or automatic driving control of the vehicle based on the output of the sensor unit 13 and the map data stored in the storage unit 12. The control unit 15 is an example of a “acquisition unit”, a “division unit”, a “specific unit”, a “compression unit” in the present invention, and a computer that executes a program in the present invention.

[Feature dictionary data]
FIG. 3A shows the data structure of the feature dictionary data 20. As shown in FIG. 3A, the feature dictionary data 20 has a template DB 22 and a parameter determination table 23.

Here, the template DB 22 is a database that records templates that are typical three-dimensional shape data of various objects that are assumed to exist around the road. When a plurality of shape patterns exist for the same type of feature, a template corresponding to each shape pattern is recorded in the template DB 22.

In the parameter determination table 23, parameters and the like to be determined are recorded for each template recorded in the template DB 22. FIG. 3B shows an example of the data structure of the parameter determination table 23. The parameter determination table 23 shown in FIG. 3B includes each item of “template”, “feature type”, and “parameter to be determined”.

In the item of "template", the identification information of the template registered in the template DB 22 is recorded. In the item of "feature type", the name of the feature type represented by the corresponding template is recorded. Here, symbols such as "x" and "y" are attached to the names of the feature types having a plurality of shape patterns, and as many records as the number of shape patterns are provided. For example, in the case of a traffic light, records of "traffic light x" and "traffic light y" are provided, and "template B" and "template C" are associated with each record.

In the item of "parameter to be decided", the parameter to be decided is specified for each corresponding template. Here, the "reference coordinates" are parameters that specify the absolute position coordinates in which the target feature exists, and are, for example, parameters that indicate the center coordinates of the target feature. Reference coordinates are defined by absolute three-dimensional coordinates such as latitude, longitude, and altitude. The "normal coordinate" is a coordinate parameter indicating the normal direction of the planar structure when the target feature is a feature having a planar structure (for example, a road sign). The normal coordinates may be, for example, three-dimensional coordinates indicating the normal direction with respect to the reference coordinates. "Scale" is a parameter related to scaling for adjusting the target template to the size of the measured feature.

In addition, in the item of "parameter to be determined", in addition to the parameters of "reference coordinates", "normal coordinates", and "scale", various parameters necessary for matching the target template to the target feature are included. It may be specified. For example, in the item of "parameter to be determined", a parameter that defines the ratio of the vertical width, the horizontal width, and the depth, a parameter that defines the interval when the repeating structure is provided, and the like may be appropriately specified. The parameter determination table 23 is an example of “setting information” in the present invention.

[Processing flow]
(1) Compression process FIG. 4 is an example of a flowchart of a compression process executed by the control unit 15 in this embodiment. The control unit 15 repeatedly executes the process of the flowchart shown in FIG.

First, the control unit 15 acquires the point cloud data output by the rider 30 (step S101). Specifically, the control unit 15 acquires point cloud data from the rider 30 that defines relative three-dimensional coordinates with respect to the vehicle at each point of the object irradiated with the pulse laser emitted by the rider 30. In this case, preferably, the control unit 15 uses the coordinates of each point of the point cloud data acquired in step S101 as the reference from the latitude, longitude, altitude, etc. from the relative three-dimensional coordinates with respect to the vehicle. Convert to absolute 3D coordinates. In this case, for example, the control unit 15 specifies the position and traveling direction of the vehicle based on the output of the sensor unit 13 and reads out the information on the installation angle of the rider 30 stored in advance in the storage unit 12, as described above. Perform coordinate conversion processing.

Next, the control unit 15 divides the point cloud data acquired in step S101 for each feature (step S102). In this case, for example, the control unit 15 has a different reflectance to the pulse laser for each feature, and the light receiving level of the pulse laser reflected by the feature is different for each feature according to the reflectance of the irradiated feature. Assuming that it is different. Then, the control unit 15 applies a known region division method or the like, and divides each point into each feature based on the light receiving level of each point in the point cloud data. In another example, the control unit 15 divides the point cloud data for each feature by applying a known image recognition process based on the color information of the image output by the camera 31, and the divided point cloud. Recognize the type of feature represented by the data. When the control unit 15 specifies the color information corresponding to each point of the point cloud data, for example, the two-dimensional coordinate system of the captured image of the camera 31 and the three-dimensional coordinate system of the point cloud data output by the rider 30. By referring to the table in which and is associated with each other in advance, the pixels of the image corresponding to each point of the point cloud data are specified.

Next, the control unit 15 identifies the template recorded in the template DB 22 corresponding to each point cloud data for each feature divided in step S102 (step S103). In the first example, the control unit 15 uses a known pattern matching technique to determine the degree of similarity between the three-dimensional shape specified from the point cloud data divided for each feature and the shape of each template recorded in the template DB 22. Calculated based on. Then, the control unit 15 identifies the template having the highest calculated similarity. The control unit 15 may appropriately change the scale of each template, change the posture (including the rotation operation), and the like when calculating the similarity. In the second example, the control unit 15 recognizes the feature represented by each point cloud data divided in step S102 without referring to the template DB 22, and identifies the template corresponding to the recognized feature. In this case, for example, the control unit 15 recognizes the type of the feature corresponding to each point cloud data by a known image recognition process based on the image output by the camera 31, and creates a template corresponding to the type of the feature. , Parameter determination table 23 and the like.

Next, the control unit 15 determines the parameters corresponding to the template specified in step S103 (step S104). Specifically, first, the control unit 15 refers to the item of "parameter to be determined" recorded in the record of the parameter determination table 23 corresponding to the template specified in step S103, and determines the type of parameter to be calculated. decide. Then, when the control unit 15 applies each parameter to be calculated to the target template and adjusts the position, size, etc. of the template, the adjusted template and the three-dimensional shape indicated by the point cloud data are obtained. Determine the value of each parameter so that is the closest approximation. In this case, the control unit 15 determines the value of each parameter so as to maximize the similarity between the template and the three-dimensional shape of the point cloud data, for example, based on a known pattern matching technique. For example, the control unit 15 stores a plurality of candidate values for each type of parameter in advance, calculates the above-mentioned similarity for all combinations of candidate values of each type of parameter, and the similarity is maximum. The combination that becomes is determined as the value of each parameter.

Then, the control unit 15 stores the identification information of the template specified in step S103 and the information related to the value of the parameter determined in step S103 (also simply referred to as “parameter information”) in association with the compressed data 21 (step). S105). In this case, since the control unit 15 does not need to store the three-dimensional point cloud data as the compressed data 21, the three-dimensional point cloud data output by the rider 30 can be compressed with a high compression rate.

After that, the compressed data 21 stored in the storage unit 12 is supplied to a server device that manages map data used for, for example, automatic operation, and is used for updating the map data.

(2) Decompression Processing FIG. 5 is a flowchart showing a procedure of decompression processing for the compressed data 21 generated by the compression processing of FIG. Here, as an example, a case where the control unit 15 performs a decompression process on the compressed data 21 stored in the storage unit 12 will be described.

First, the control unit 15 refers to the compressed data 21 and extracts a combination of template identification information and parameter information for a specific feature (step S201). For example, the control unit 15 extracts a combination of the identification information and the parameter information of the template corresponding to the feature existing within a predetermined distance from the own vehicle position recognized based on the output of the sensor unit 13. In this case, for example, the control unit 15 refers to the reference coordinates included in the parameter information and specifies the position of the feature corresponding to the combination of the identification information of the template and the parameter information, so that the control unit 15 is within a predetermined distance from the position of the own vehicle. Identify the features that exist in.

Next, the control unit 15 approximately restores the three-dimensional data of the target feature based on the combination of the identification information and the parameter information of the template extracted in step S202 (step S202). In this case, first, the control unit 15 extracts the template from the template DB 22 of the feature dictionary data 20 from the identification information of the template for each combination of the identification information and the parameter information of the template. Then, the control unit 15 reconstructs the three-dimensional data of each object by adjusting the position and scaling of the extracted template based on the parameters such as the reference coordinates and the scale included in the corresponding parameter information.

In this way, the control unit 15 can approximately restore the data compressed using the feature dictionary data 20 by referring to the feature dictionary data 20 again. In this example, the in-vehicle device 1 is an example of the "data decompression device" in the present invention.

As described above, the vehicle-mounted device 1 according to the present embodiment stores the feature dictionary data 20, acquires the point cloud data output by the rider 30 including the feature in the measurement range, and obtains the point cloud data. Is compressed and stored as compressed data 21. At this time, the in-vehicle device 1 generates a parameter for approximating the point cloud data with a template representing the outer shape of the feature with respect to the point cloud data corresponding to the feature registered in the feature dictionary data 20. To do. Then, the vehicle-mounted device 1 stores the parameter information indicating the generated parameters as compressed data 21 in association with the identification information of the template. As a result, the vehicle-mounted device 1 can suitably compress the point cloud data output by the rider 30.

[Modification example]
Next, a modification suitable for the embodiment will be described. The following modifications may be applied to the above-described embodiment in any combination.

(Modification example 1)
The in-vehicle device 1 may decompress the compressed data compressed by another device with reference to the feature dictionary data 20 according to the processing of the flowchart of FIG. 5, and the decompressed data may be used for route guidance, automatic operation, or the like.

FIG. 6 shows a configuration example of a data compression system that exchanges compressed data via the server device 4. In the example of FIG. 6, the vehicle-mounted device 1A has the same configuration as the vehicle-mounted device 1 shown in FIG. 2, and the server device 4 receives and stores the compressed data generated by the vehicle-mounted device 1A. Although only one on-board unit 1A is shown in FIG. 6, a plurality of on-board units 1A actually exist and are mounted on different vehicles. Then, the vehicle-mounted device 1A generates compressed data according to the flowchart of FIG. 4, and supplies the generated compressed data to the server device 4. The on-board unit 1B stores at least the template DB 22, and for example, by transmitting a predetermined request signal specifying the current position information or the like to the server device 4, compression corresponding to the feature around the own vehicle position is performed. Data is received from the server device 4. Then, the in-vehicle device 1B decompresses by referring to the feature dictionary data 20 according to the flowchart of FIG. 5, and generates three-dimensional data of the features around the position of the own vehicle. Then, the vehicle-mounted device 1B executes route guidance, automatic driving control of the vehicle, and the like according to the generated three-dimensional data.

As described above, a device other than the device that generated the compressed data may perform the decompression process of the compressed data according to the flowchart of FIG. 5, and may be used for various purposes such as route guidance and automatic driving control of the vehicle. In the example of FIG. 6, the on-board unit 1B is an example of the "data decompression device" in the present invention.

(Modification 2)
The processing of the flowchart of FIG. 4 may be executed by a server device capable of data communication with the vehicle-mounted device 1. FIG. 7 shows an outline of the data compression system according to this modified example.

The data compression system shown in FIG. 7 includes a server device 4 that performs data communication with the vehicle-mounted device 1. Although only one on-board unit 1 is shown in FIG. 7, a plurality of on-board units 1 actually perform data communication with the server device 4. The server device 4 includes feature dictionary data 20 and compressed data 21. Then, the server device 4 receives the point cloud data output by the rider 30 from the vehicle-mounted device 1. In this case, the server device 4 executes steps S102 to S105 of the flowchart of FIG. 4 by referring to the feature dictionary data 20, and stores the compressed data as compressed data 21. The server device 4 further receives information such as the vehicle position, the traveling direction, and the installation angle of the rider 30 from the vehicle-mounted device 1, and based on these information, the point cloud data received from the vehicle-mounted device 1 is used to transmit the vehicle. Relative 3D coordinates as a reference may be converted to absolute 3D coordinates. Instead, the server device 4 may receive the point cloud data converted into absolute three-dimensional coordinates from the vehicle-mounted device 1.

In another example, the processing of the flowchart of FIG. 4 may be executed by a control unit (ECU: Electronic Control Unit) of the vehicle instead of the vehicle-mounted device 1. In this case, the vehicle control unit electrically connects to various sensors including the rider 30 and executes the flowchart of FIG. 4 by referring to the feature dictionary data 20 stored in the predetermined storage unit. Then, the control unit of the vehicle generates the compressed data 21 and stores it in the storage unit.

(Modification example 3)
The vehicle-mounted device 1 may compress and store the three-dimensional data generated based on the output of the camera 31 instead of storing the compressed data 21 in which the output of the rider 30 is compressed.

In this case, for example, the camera 31 is a three-dimensional measurement camera having a plurality of image pickup elements, and the control unit 15 generates three-dimensional data having RGB values based on the output of the camera 31. Then, steps S102 to S105 of the flowchart of FIG. 4 are executed to generate compressed data 21 composed of a combination of template identification information and parameter information. In this way, the vehicle-mounted device 1 may perform compression processing on the three-dimensional data obtained from the output of the external sensor other than the rider 30.

(Modification example 4)
When the control unit 15 determines that features having the same or similar outer shapes (also referred to as “common outer shape features”) are close to each other within a predetermined distance, the identification information and parameter information of the templates of the individual features Instead of storing the combination of the above as compressed data 21, these relative positional relationships may be stored.

For example, when compressing the point cloud data of a common external feature, the control unit 15 sets the identification information and parameter information of a template of one reference feature (also referred to as “reference feature”), and the reference feature. The relative position (for example, the difference in latitude and longitude) from the to the other external common features is stored as the compressed data 21. That is, the control unit 15 stores the identification information and the parameter information of the template only for the reference feature, and for other common external features, only the information of the relative position from the reference feature is used as the compressed data 21. Remember. The reference feature may be randomly selected from the common features of the outer shape, or may be selected based on a predetermined rule. By doing so, the control unit 15 reduces the data capacity of the compressed data 21 to be stored as compared with the case where the identification information and the parameter information of the individual templates of the common external features are stored as the compressed data 21. can do.

1 In-vehicle device 4 Server device 11 Communication unit 12 Storage unit 13 Sensor unit 14 Input unit 15 Control unit 16 Output unit 20 Feature dictionary data 21 Compressed data

Claims (9)

A storage unit that stores a template that represents the outline of a feature,
An acquisition unit that acquires measurement data output by the measuring device,
A compression unit that generates compressed data obtained by compressing the measurement data is provided.
The compression unit is a data compression device that generates, as compression data, parameters for approximating the measurement data with a template representing the outer shape of the feature with respect to the measurement data corresponding to the feature. The data compression device according to claim 1, wherein the compression unit generates at least a parameter representing the position of a feature measured by the measuring device and a parameter for adjusting the size of the template as the parameters. The storage unit stores setting information that defines parameters to be generated for each template.
The data compression device according to claim 1 or 2, wherein the compression unit determines a parameter to be generated with respect to the measurement data corresponding to the feature based on the setting information. A division unit that divides the measurement data acquired by the acquisition unit for each feature, and a division unit.
For each measurement data divided by the division unit, a specific unit that specifies the corresponding template and a specific unit
The data compression device according to any one of claims 1 to 3. The data compression device according to any one of claims 1 to 4, wherein the measuring device moves together with the moving body and generates measurement data of features existing around the moving body. A storage unit that stores a parameter generated by the data compression device according to any one of claims 1 to 5 and a template corresponding to the parameter.
A decompression unit that generates approximate data of measurement data based on the parameters stored in the storage unit and the template.
A data decompression device equipped with. A control method executed by a data compression device having a storage unit that stores a template representing the outer shape of a feature.
The acquisition process to acquire the measurement data output by the measuring device,
It has a compression step of generating compressed data obtained by compressing the measurement data.
The compression step is a control method for generating as the compressed data parameters for approximating the measurement data with a template representing the outer shape of the feature with respect to the measurement data corresponding to the feature. A program executed by a computer that refers to a storage unit that stores a template that represents the outline of a feature.
An acquisition unit that acquires measurement data output by the measuring device,
The computer is made to function as a compression unit that generates compressed data obtained by compressing the measurement data.
The compression unit is a program that generates, as the compressed data, parameters for approximating the measurement data with a template representing the outer shape of the feature with respect to the measurement data corresponding to the feature. A storage medium that stores the program according to claim 8.

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