Information processing device, information processing method, and computer program

Abstract

An information processing device 1 comprises an acquisition unit 11 that acquires target three-dimensional data, a curvature calculation unit 12 that calculates curvature information indicating a curvature of a target surface on the basis of the three-dimensional data, a first position calculation unit 13 that calculates curvilinear coordinates at a plurality of first positions on the target surface on the basis of the curvature information, and a reconstruction unit 14 including a second position calculation unit 141 that calculates curvilinear coordinates at a plurality of second positions different from the plurality of first positions on the target surface on the basis of the curvature information and the curvilinear coordinates of the plurality of first positions and a generation unit 142 that generates a surface image indicating the target surface on the basis of the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.

Description

Information processing device, information processing method, and recording medium

[0001] The present disclosure relates to the technical fields of an information processing device, an information processing method, and a recording medium.

[0002] Patent Literature 1 describes a technique for acquiring choroidal information from a fundus image of a subject's eye and comparing the choroidal information with a standard choroidal database to determine whether or not there is an abnormality in the fundus. Patent Literature 2 describes a technique for acquiring three-dimensional optical coherence tomography (OCT) data for intraoral features, sampling at least one dimension pseudo-randomly or randomly, reconstructing an image volume of the intraoral features using compressed sensing, where the data density of the reconstructed image volume is greater than the data density of the acquired OCT data in the at least one dimension or by a corresponding transformation, and rendering the reconstructed image volume for display. Patent Literature 3 describes a technique for obtaining a tomographic image from combined light obtained by irradiating the subject's eye with measurement light and combining the returned light with a reference light, the technique including a first step of measuring the distance between the subject's eye and an objective lens, a second step of acquiring a tomographic image of the subject's eye, a third step of setting a region for calculating the curvature of the tomographic image, and a fourth step of calculating the curvature of the set region using the measured distance. a setting unit that sets a curvilinear coordinate system that forms a curved surface formed by a first group of intersections between a group of longitudinal sections that are approximately parallel to the distal axis direction and the finger surface and a second group of intersections between a group of transverse sections that are approximately perpendicular to the group of longitudinal sections and the finger surface; a fingerprint image data acquisition unit that acquires fingerprint image data expressed in a predetermined planar coordinate system; and a matching data acquisition unit that obtains intermediate data expressed in the curvilinear coordinate system from the fingerprint image data and obtains matching data expressed in a coordinate system of a virtual plane obtained by virtually unfolding a curved surface corresponding to the curvilinear coordinate system from the intermediate data, and acquires matching data that takes the posture of the finger into consideration, thereby improving matching accuracy.

[0003] JP 2020-058647 A JP 2019-518936 A JP 2012-147977 A JP 2006-172258 A

[0004] An object of this disclosure is to provide an information processing device, an information processing method, and a recording medium that aim to improve upon the techniques described in prior art documents.

[0005] One aspect of the information processing device comprises reconstruction means including an acquisition means for acquiring three-dimensional data of an object, a curvature calculation means for calculating curvature information indicating the curvature of the surface of the object based on the three-dimensional data, a first position calculation means for calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information, a second position calculation means for calculating curvilinear coordinates of a plurality of second positions on the surface of the object that are different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions, and a generation means for generating a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.

[0006] One aspect of the information processing method includes acquiring three-dimensional data of an object, calculating curvature information indicating the curvature of the surface of the object based on the three-dimensional data, calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information, calculating curvilinear coordinates of a plurality of second positions on the surface of the object that are different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions, and generating a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.

[0007] One aspect of the recording medium has recorded thereon a computer program for causing a computer to execute an information processing method that acquires three-dimensional data of an object, calculates curvature information indicating the curvature of the surface of the object based on the three-dimensional data, calculates curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information, calculates curvilinear coordinates of a plurality of second positions on the surface of the object that are different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions, and generates a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.

[0008] FIG. 1 is a block diagram showing the configuration of an information processing device according to a first embodiment. FIG. 2 is a block diagram showing the configuration of an information processing device according to a second embodiment. FIG. 3 is a conceptual diagram showing the relationship between three-dimensional spatial coordinates and curvilinear coordinates. FIG. 4(a) shows a curved image, and FIG. 4(b) shows a two-dimensional image obtained by projecting three-dimensional data onto a plane. FIG. 5 is a flowchart showing the flow of information processing operations performed by an information processing device according to a second embodiment. FIG. 6 is a conceptual diagram of information processing operations performed by an information processing device according to a third embodiment. FIG. 7 is a flowchart showing the flow of information processing operations performed by an information processing device according to a fourth embodiment. FIG. 8 is a block diagram showing the configuration of an information processing device according to a fifth embodiment. FIG. 9 is a flowchart showing the flow of information processing operations performed by an information processing device according to the fifth embodiment. FIG. 10 is a block diagram showing the configuration of an information processing device according to a sixth embodiment. FIG. 11 is a flowchart showing the flow of information processing operations performed by an information processing device according to the sixth embodiment. FIG. 12 is a block diagram showing the configuration of an information processing device according to a seventh embodiment. FIG. 13 is a flowchart showing the flow of information processing operations performed by an information processing device according to the seventh embodiment.

[0009] Hereinafter, embodiments of an information processing device, an information processing method, and a recording medium will be described with reference to the drawings. [1: First Embodiment]

[0010] A first embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the first embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 1 to which the first embodiment of the information processing device, the information processing method, and the recording medium is applied. [1-1: Configuration of Information Processing Device 1]

[0011] The configuration of an information processing device 1 in the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the information processing device 1 in the first embodiment.

[0012] As shown in FIG. 1 , the information processing device 1 includes an acquisition unit 11, a curvature calculation unit 12, a first position calculation unit 13, and a reconstruction unit 14. The acquisition unit 11 acquires three-dimensional data of an object. The curvature calculation unit 12 calculates curvature information indicating the curvature of the surface of the object based on the three-dimensional data. The first position calculation unit 13 calculates curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information. The reconstruction unit 14 includes a second position calculation unit 141 and a generation unit 142. The second position calculation unit 141 calculates curvilinear coordinates of a plurality of second positions on the surface of the object, which are different from the plurality of first positions, based on the curvature information and the curvilinear coordinates of the plurality of first positions. The generation unit 142 generates a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions. [1-2: Technical Effects of the Information Processing Device 1]

[0013] The information processing device 1 in the first embodiment can generate a curved image showing the surface of an object based on the curvilinear coordinates of a plurality of first positions and the curvilinear coordinates of a plurality of second positions. That is, the information processing device 1 can generate a desired curved image, i.e., a high-precision curved image of the object, based on three-dimensional data related to a plurality of first positions, which is a number smaller than the number of positions from which three-dimensional information required for generating the curved image is desired. [2: Second Embodiment]

[0014] A second embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the second embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 2 to which the second embodiment of the information processing device, the information processing method, and the recording medium is applied. [2-1: Configuration of Information Processing Device 2]

[0015] The configuration of the information processing device 2 in the second embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the configuration of the information processing device 2 in the second embodiment.

[0016] 2 , the information processing device 2 includes a calculation device 21 and a storage device 22. Furthermore, the information processing device 2 may include an optical coherence tomography imaging device 100, a communication device 23, an input device 24, and an output device 25. However, the information processing device 2 does not have to include at least one of the optical coherence tomography imaging device 100, the communication device 23, the input device 24, and the output device 25. If the information processing device 2 does not include the optical coherence tomography imaging device 100, the information processing device 2 may transmit and receive information to and from the optical coherence tomography imaging device 100 via the communication device 23. The calculation device 21, the storage device 22, the optical coherence tomography imaging device 100, the communication device 23, the input device 24, and the output device 25 may be connected via a data bus 26.

[0017] The arithmetic device 21 includes, for example, at least one of a central processing unit (CPU), a graphics processing unit (GPU), and a field programmable gate array (FPGA). The arithmetic device 21 reads a computer program. For example, the arithmetic device 21 may read a computer program stored in the storage device 22. For example, the arithmetic device 21 may read a computer program stored in a computer-readable, non-transitory storage medium using a storage medium reading device (e.g., an input device 24, described later) not shown in the drawings that is included in the information processing device 2. The arithmetic device 21 may acquire (i.e., download or read) the computer program from a device (not shown) located outside the information processing device 2 via the communication device 23 (or another communication device). The arithmetic device 21 executes the read computer program. As a result, logical functional blocks for executing the operations to be performed by the information processing device 2 are realized within the arithmetic device 21. In other words, the arithmetic device 21 can function as a controller for realizing logical functional blocks for executing the operations (in other words, processing) to be performed by the information processing device 2.

[0018] 2 shows an example of logical functional blocks implemented within the arithmetic device 21 to execute information processing operations. As shown in FIG. 2, the arithmetic device 21 implements an acquisition unit 211, which is a specific example of an "acquisition means" described in the appendix below, a curvature calculation unit 212, which is a specific example of a "curvature calculation means" described in the appendix below, a first position calculation unit 213, which is a specific example of a "first position calculation means" described in the appendix below, and a reconstruction unit 214, which is a specific example of a "reconstruction means" described in the appendix below. The operations of the acquisition unit 211, the curvature calculation unit 212, the first position calculation unit 213, and the reconstruction unit 214 will be described later with reference to FIGS. 3 to 5.

[0019] The storage device 22 can store desired data. For example, the storage device 22 may temporarily store a computer program executed by the arithmetic device 21. The storage device 22 may temporarily store data that the arithmetic device 21 temporarily uses when the arithmetic device 21 is executing a computer program. The storage device 22 may store data that the information processing device 2 stores long-term. The storage device 22 may include at least one of a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device. In other words, the storage device 22 may include a non-temporary recording medium.

[0020] The communication device 23 is capable of communicating with devices external to the information processing device 2 via a communication network (not shown). The communication device 23 may be a communication interface based on standards such as Ethernet (registered trademark), Wi-Fi (registered trademark), Bluetooth (registered trademark), or USB (Universal Serial Bus). If the communication device 23 is a communication interface based on the USB standard, the communication device 23 may be capable of communicating between, for example, the arithmetic device 21 including an FPGA and a mechanism including a computer that controls the entire information processing device 2.

[0021] The input device 24 is a device that accepts information input to the information processing device 2 from outside the information processing device 2. For example, the input device 24 may include an operation device (for example, at least one of a keyboard, a mouse trackball, a touch panel, a pointing device such as a pen tablet, a button, etc.) that can be operated by an operator of the information processing device 2. For example, the input device 24 may include a reading device that can read information recorded as data on a recording medium that can be externally attached to the information processing device 2.

[0022] The output device 25 is a device that outputs information to the outside of the information processing device 2. For example, the output device 25 may output information as an image. That is, the output device 25 may include a display device (a so-called display) capable of displaying an image showing the information to be output. Examples of display devices include a liquid crystal display and an OLED (organic light-emitting diode) display. For example, the output device 25 may output information as sound. That is, the output device 25 may include an audio device (a so-called speaker) capable of outputting sound. For example, the output device 25 may output information on paper. That is, the output device 25 may include a printing device (a so-called printer) capable of printing desired information on paper. Furthermore, the input device 24 and the output device 25 may be integrally formed as a touch panel.

[0023] Note that the hardware configuration shown in FIG. 2 is an example, and devices other than those shown in FIG. 2 may be added, or some devices may not be provided. Also, some devices may be replaced with other devices having similar functions. Also, some functions of the second embodiment may be provided by other devices via a network. The functions of the second embodiment may be distributed and realized among multiple devices. In this way, the hardware configuration shown in FIG. 2 can be modified as appropriate.

[0024] In the second embodiment, the three-dimensional data may be three-dimensional brightness data generated by performing optical coherence tomography imaging by irradiating a target with a light beam while scanning it two-dimensionally. [2-2: Optical coherence tomography imaging device 100]

[0025] The optical coherence tomography imaging apparatus 100 performs optical coherence tomography imaging by irradiating a target with a light beam while performing two-dimensional scanning, and generates three-dimensional brightness data of the target.

[0026] Optical coherence tomography (OCT) is a technology that utilizes the interference between object light and reference light to identify the position of the light scattering point where the object light is scattered in the object in the optical axis direction, i.e., the depth direction of the object, and obtain spatially resolved structural data in the depth direction inside the object. Optical coherence tomography technologies include time domain (TD-OCT) and Fourier domain (FD-OCT). In FD-OCT, when object light and reference light are made to interfere with each other, the interference light spectrum over a wide wavelength band is measured, and this is Fourier transformed to obtain structural data in the depth direction. Methods for obtaining the interference light spectrum include spectral domain (SD-OCT), which uses a spectroscope, and swept source (SS-OCT), which uses a light source that sweeps the wavelength. The following explanation will be given using an example in which the optical coherence tomography imaging device 100 performs optical coherence tomography scanning using the SS-OCT method, but the target three-dimensional brightness data is not limited to that obtained using the SS-OCT method, and may also be that obtained using the above-mentioned TD-OCT method or SD-OCT method.

[0027] The optical coherence tomography imaging apparatus 100 scans the irradiation position of the object light in an in-plane direction perpendicular to the depth direction of the object, thereby obtaining tomographic structure data that is spatially resolved in the in-plane direction and in the depth direction, i.e., three-dimensional tomographic structure data of the object to be measured. The optical coherence tomography imaging apparatus 100 may include a light source, a scanner unit, and a signal processing unit.

[0028] The light source may emit light while sweeping the wavelength. The optical coherence tomography imaging apparatus 100 may split the light emitted from the light source into object light and reference light. The scanner unit irradiates the object light onto an object and scatters it. The object light scattered from the object and the reference light reflected by the reference light mirror interfere with each other, generating two interference lights. That is, the intensity ratio of the two interference lights is determined by the phase difference between the object light and the reference light. The scanner unit outputs an electrical signal corresponding to the intensity difference between the two interference lights to a signal processing unit.

[0029] The signal processing unit converts the electrical signal output by the scanner unit into data. The signal processing unit performs a Fourier transform on the generated interference light spectrum data to obtain data indicating the intensity of backscattered light (object light) at different depth positions in the depth direction (also referred to as the "Z direction"). The operation of obtaining data indicating the intensity of backscattered light (object light) in the depth direction (Z direction) of the irradiation position of the object light in the target is called an "A scan." The signal processing unit generates a waveform indicating the object light backscattering intensity at Nz locations as an A scan waveform.

[0030] The scanner unit scans the irradiation position of the object light on the target, and moves the irradiation position of the object light in the scanning line direction (also referred to as the "scanning fast axis direction" and "X direction").

[0031] The signal processing unit repeatedly performs an A-scan operation for each irradiation position of the object light and connects the A-scan waveforms for each irradiation position of the object light. As a result, the signal processing unit acquires a two-dimensional map of the intensity of backscattered light (object light) in the scanning line direction (X direction) and the depth direction (Z direction) as a tomographic image. Hereinafter, the operation of repeatedly performing A-scan operations while moving in the scanning line direction (the fast axis direction of scanning, X direction) and connecting the measurement results is referred to as a "B scan." If the irradiation positions of the object light for each B scan are Nx locations, the tomographic image obtained by the B scan is two-dimensional brightness data indicating the backscattered intensity of the object light at Nz × Nx points.

[0032] The scanner unit moves the irradiation position of the object light not only in the scanning line direction (X direction) but also in a direction perpendicular to the scanning line (also called the "slow axis direction of scanning" or "Y direction"). The signal processing unit repeatedly performs B-scan operations and connects the B-scan measurement results. In this way, the signal processing unit acquires three-dimensional tomographic structure data. Hereinafter, the operation of repeatedly performing B-scan operations while moving in the direction perpendicular to the scanning line (Y direction) and connecting the measurement results will be referred to as a "C scan." If the number of B-scans performed per C scan is Ny, the tomographic structure data obtained by the C scan is three-dimensional brightness data that indicates the backscattering intensity of the object light at Nz × Nx × Ny points.

[0033] The signal processing unit sends the data after the digitalization process to the arithmetic unit 21. Note that the operation of the signal processing unit may be performed by the arithmetic unit 21. [2-3: Information processing operation performed by the information processing device 2]

[0034] The flow of information processing operations performed by the information processing device 2 in the second embodiment will be described with reference to Figures 3 to 5. Figure 3 is a conceptual diagram showing the relationship between three-dimensional spatial coordinates and curvilinear coordinates.

[0035] As shown in Figure 3, even if the intervals between measurement positions in the spatial coordinates (X, Y) are uniform, the intervals between measurement positions in the corresponding curvilinear coordinates (s, t) are irregular, which causes distortion in the extracted image.

[0036] 4(a) shows a curved surface image of an object, and FIG. 4(b) shows a conceptual diagram of a two-dimensional image obtained by orthogonally projecting the curved surface of the object onto a tangent plane at the highest point of the curved surface. That is, as shown in FIG. 4(a), an example is given in which the distances L1 and L2, L2 and L3, and L3 and L4 are equal on the object's surface (curved surface). In this case, when the object's surface (curved surface) is projected onto a plane, the distances L1 and L2, L2 and L3, and L3 and L4 become smaller with increasing distance from the center, as shown in FIG. 4(b).

[0037] 5 is a flowchart showing the flow of information processing operations performed by the information processing device 2 in the second embodiment. As shown in Fig. 5, the acquisition unit 211 acquires three-dimensional luminance data generated by performing optical coherence tomography imaging by irradiating a target with a light beam while scanning it two-dimensionally (step S20).

[0038] The curvature calculation unit 212 calculates curvature information indicating the curvature of the surface of the object based on the three-dimensional luminance data (step S21). The curvature calculation unit 212 may extract a curved surface corresponding to the surface of the object based on the three-dimensional luminance data. If the object is a finger, the curved surface may be at least one of a curved surface shape corresponding to the epidermis and a curved surface corresponding to the dermis. The curvature calculation unit 212 may detect the main curvature of the extracted curved surface. The main curvature may be, for example, a rough curvature of the curved surface that ignores fine irregularities such as skin patterns.

[0039] The first position calculation unit 213 calculates curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information (step S22). Each of the plurality of first positions may correspond to a respective one of a plurality of object beam irradiation positions by the optical coherence tomography imaging apparatus 100. The first positions may be positions on the curved surface acquired based on an A-scan operation of the optical coherence tomography imaging apparatus 100 on the object beam irradiation positions. The first position calculation unit 213 may calculate the curvilinear coordinates of each of the first positions based on the spatial coordinates of each of the first positions and the curvature information.

[0040] The second position calculation unit 2141 calculates curvilinear coordinates of a plurality of second positions on the surface of the object that are different from the plurality of first positions, based on the curvature information and the curvilinear coordinates of the plurality of first positions (step S23).

[0041] The generating unit 2142 generates a curved image showing the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions (step S24). The information processing operation performed by the information processing device 2 in the second embodiment may be likened to the operation of creating a planar map based on a spherical globe. [2-4: Technical Effects of the Information Processing Device 2]

[0042] The optical coherence tomography imaging time is determined depending on the A-scan capability of the optical coherence tomography imaging device 100 and the number of positions to be irradiated. For example, if an optical coherence tomography imaging device 100 capable of A-scanning 400,000 positions per second is used to scan approximately 87,000 positions (295 positions in the X direction and 295 positions in the Y direction) to obtain one image, the optical coherence tomography imaging time will be approximately 0.22 seconds. The subject may move during this 0.22 second period, and if the subject moves, the accuracy of the image will decrease. For this reason, it is desirable to shorten the optical coherence tomography imaging time. However, it is relatively difficult to shorten the time required for an A-scan.

[0043] The information processing device 2 in the second embodiment can generate a curved surface image showing the surface of an object based on the curvilinear coordinates of multiple first positions where A-scans were actually performed and the curvilinear coordinates of multiple second positions where A-scans were not actually performed. That is, the information processing device 2 can generate a desired curved surface image, i.e., a high-precision curved surface image of the object, based on three-dimensional intensity data obtained by A-scans at a number of positions fewer than the number of positions at which the three-dimensional information required to generate the curved surface image is desired. In other words, the information processing device 2 can acquire a curved surface image with a resolution higher than the resolution of the three-dimensional data. Therefore, the information processing device 2 can acquire a high-precision curved surface image, shorten the optical coherence tomography imaging time, and prevent a decrease in image accuracy due to object motion. The operation of the information processing device 2 can be achieved using a general optical coherence tomography imaging device, and does not require special scanning or control techniques. [3: Third Embodiment]

[0044] An information processing device, an information processing method, and a recording medium according to a third embodiment will be described below. The third embodiment of the information processing device, the information processing method, and the recording medium will be described below using an information processing device 3 to which the third embodiment of the information processing device, the information processing method, and the recording medium is applied.

[0045] The information processing device 3 in the third embodiment differs from the information processing device 2 in the second embodiment in the second position calculation operation by the second position calculation unit 2141. Other features of the information processing device 3 may be the same as other features of the information processing device 2. Therefore, hereinafter, differences from the already described embodiments will be described in detail, and descriptions of other overlapping parts will be omitted as appropriate. [3-1: Second position calculation operation by information processing device 3]

[0046] As illustrated in FIG. 6, in the third embodiment, the target of optical coherence tomography imaging may be, for example, a finger.

[0047] As shown in FIG. 6A, even if the distance d on the XY plane is constant, the distances on the curved surface are non-uniform, as exemplified by distances d1 and d2.

[0048] Fig. 6(b) is a conceptual diagram illustrating raw data obtained by optical coherence tomography. The relatively fine irregularities in Fig. 6(b) may represent skin patterns. The curved surface illustrated in Fig. 6(b) may correspond to at least one of the shape of the epidermis and the shape of the dermis.

[0049] Fig. 6(c) is a conceptual diagram in which the spatial coordinates of the conceptual diagram illustrated in Fig. 6(b) are converted into curvilinear coordinates. In the curvilinear coordinate system, it can be seen that the distance from the center increases in the left-right direction. This corresponds to the fact that the distance d2 is larger than the distance d1 illustrated in Fig. 6(a). Comparing Fig. 6(b) and Fig. 6(c) reveals that the greater the curvature of the surface of the object, the larger the distance in the left-right direction.

[0050] 6(d) illustrates an example of a curved surface image including the first positions obtained by the measurement. As illustrated in FIG. 6(d), the plurality of first positions are present non-uniformly and / or irregularly on the curved surface corresponding to the surface of the object. More specifically, the plurality of first positions are present less frequently on the curved surface as they are further away from the center.

[0051] In the third embodiment, the second position calculation unit 2141 calculates the curvilinear coordinates of the second positions based on the curvature information and the curvilinear coordinates of the plurality of first positions, so that the greater the curvature of the area on the surface of the object, the more curvilinear coordinates of the second positions are calculated. Fig. 6(e) illustrates an example of a curved surface image generated by the generation unit 2142 based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions calculated by the second position calculation unit 2141. As illustrated in Fig. 6(e), the information processing device 3 in the third embodiment can obtain a high-resolution image in which a plurality of positions, including a plurality of first positions and a plurality of second positions, are uniformly and regularly arranged. [3-2: Technical Effects of the Information Processing Device 3]

[0052] In many cases, it is easier to control the scanning positions to be evenly spaced than to control the scanning positions to be unevenly spaced. In contrast, if the surface of the target is curved, scanning evenly spaced positions will result in the scanned positions being unevenly spaced in the curved surface image. The information processing device 3 in the third embodiment can generate a high-resolution curved surface image in which multiple positions, including multiple first positions and multiple second positions, are uniformly and regularly spaced. [4: Fourth Embodiment]

[0053] A fourth embodiment of an information processing device, an information processing method, and a recording medium will be described below. The fourth embodiment of the information processing device, the information processing method, and the recording medium will be described below using an information processing device 4 to which the fourth embodiment of the information processing device, the information processing method, and the recording medium is applied.

[0054] The information processing device 4 in the fourth embodiment differs from the information processing device 2 in the second embodiment and the information processing device 3 in the third embodiment in the reconstruction operation by the reconstruction unit 214. Other features of the information processing device 4 may be the same as other features of at least one of the information processing device 2 and the information processing device 3. Therefore, hereinafter, differences from the embodiments already described will be described in detail, and descriptions of other overlapping parts will be omitted as appropriate. [4-1: Compressed Sensing]

[0055] When capturing an image of a natural object, several assumptions can be made regarding pixel brightness. Natural objects often change smoothly, so brightness changes primarily smoothly. Also, depending on the structure of the object, it is highly likely that some pattern will emerge in the brightness changes. It can be assumed that brightness changes suddenly at the edge of the object, but that there is continuity in the brightness changes along that edge.

[0056] For example, if the object is a fingerprint, the ridges of the print have periodicity. Applying a cosine transform to an image with this periodicity results in an image with sparse characteristics, with few frequency components. This sparse image can also be called a sparse representation. A sparse representation has few non-zero components and many zero components.

[0057] Compressed sensing takes advantage of the property that sparse representations have few non-zero components and many zero components. Specifically, it takes advantage of the property that a sparse representation equivalent to a sparse representation extracted from an image using all pixels (called the "original image") can be extracted from an image that does not use all pixels or has irregular pixel spacing (also called an "irregularly sampled curved image"). The original image may be a high-resolution curved image.

[0058] When an inverse transform of transform 1 (referred to as "transform 2") is applied to a sparse representation extracted by transforming an original image (referred to as "transform 1"), the original image can be reconstructed. The sparse representation can also be transformed (transform 3) to reconstruct an image that does not use all of the pixels of the image. A sparse representation can also be extracted by optimizing the sparse representation so that an image that does not use all of the pixels of the image can be accurately reconstructed when transform 3 is applied. Then, when transform 2 is applied to the extracted sparse representation, an image equivalent to the original image can be reconstructed. That is, by applying compressed sensing, an image equivalent to the original image can be reconstructed based on an image that does not use all of the pixels of the image. For example, transform 1 may be a uniform cosine transform, and in this case, transform 2 may be an inverse uniform cosine transform. Furthermore, for example, transform 3 may be an inverse non-uniform cosine transform. [4-2: Information Processing Operation by Information Processing Device 4]

[0059] As shown in FIG. 7 , the acquisition unit 211 acquires three-dimensional luminance data generated by performing optical coherence tomography imaging by irradiating an object with a light beam while performing two-dimensional scanning (step S20). The curvature calculation unit 212 calculates curvature information indicating the curvature of the object's surface based on the three-dimensional luminance data (step S21). The first position calculation unit 213 calculates curvilinear coordinates of multiple first positions on the object's surface based on the curvature information (step S22). As described above, each of the multiple first positions may correspond to each of multiple object beam irradiation positions by the optical coherence tomography imaging device 100. The first positions may be positions on the curved surface acquired based on an A-scan operation of the optical coherence tomography imaging device 100 on the object beam irradiation positions. Hereinafter, the first positions will be referred to as measurement positions as appropriate. The first position calculation unit 213 may calculate the curvilinear coordinates of each measurement position based on the spatial coordinates of each measurement position and the curvature information.

[0060] The reconstruction unit 214 generates a curved surface image based on the curvilinear coordinates of each first position (step S40). When the spatial coordinates of the measurement positions are projected onto a plane, the measurement positions correspond to the irradiation positions of the object light and exist uniformly. In contrast, on a curved surface corresponding to the surface of the target, the curvilinear coordinates of the measurement positions exist non-uniformly and / or irregularly. Therefore, the curvilinear coordinates of the measurement positions are also referred to as irregularly sampled coordinates. Furthermore, a curved surface image generated from the measurement positions is also referred to as an irregularly sampled curved surface image. In other words, the reconstruction unit 214 may generate an irregularly sampled curved surface image based on each irregularly sampled coordinate.

[0061] The reconstruction unit 214 generates a feature image of the irregularly sampled surface image (step S41). The features constituting the feature image may be numerical values ​​obtained from the three-dimensional luminance data, and the numerical values ​​may be, for example, values ​​indicating luminance, depth, density, etc.

[0062] The reconstruction unit 214 converts the sparse representation x of the surface image into the irregularly sampled surface image y ｓａｍｐｌｅ Transformation matrix A to convert ｓａｍｐｌｅ is defined (step S42). [Equation 1] Irregularly sampled surface image yｓａｍｐｌｅ may be the curved surface image generated in step S40. ｓａｍｐｌｅ For example, an inverse non-uniform cosine transform may be defined as follows: ｓａｍｐｌｅ may be a transformation corresponding to transformation 3 above.

[0063] The reconstruction unit 214 extracts a sparse representation x that optimizes a loss function that determines sparsity (step S43). For example, lasso regression (least absolute shrinkage and selection operator: LASSO) may be adopted as the loss function. The reconstruction unit 214 may extract a sparse representation x that minimizes the following equation 2: [Equation 2]

[0064] The reconstructor 214 converts the sparse representation x into a high-resolution curved image in curvilinear coordinates (step S44). The reconstructor 214 may convert the sparse representation into a high-resolution curved image in curvilinear coordinates by applying a transformation corresponding to the above-described Transformation 2. The reconstructor 214 may perform the inverse transformation by employing, for example, an inverse uniform cosine transform.

[0065] That is, the reconstruction unit 214 applies compressed sensing to generate a curved surface image (steps S40 to S44). The reconstruction unit 214 may apply compressed sensing to the irregularly sampled curved surface image to reconstruct a high-resolution curved surface image that is uniformly positioned in curvilinear coordinates. The reconstruction unit 214 may apply compressed sensing to the irregularly sampled curved surface image to reconstruct a curved surface image equivalent to the original high-resolution image. [4-3: Technical Effects of the Information Processing Device 4]

[0066] The information processing device 4 in the fourth embodiment applies compressed sensing to the calculated curvature information and curvilinear coordinates to generate a curved surface image. That is, the information processing device 4 applies compressed sensing to a two-dimensional image. Therefore, compared to when compressed sensing is applied to three-dimensional luminance data including information on Nz x Nx x Ny points, the amount of calculation required for the operation performed by the information processing device 4 is small, and the processing load is light. The information processing device 4 can generate a highly accurate curved surface image with a relatively small amount of calculation and a relatively light processing load. [5: Fifth Embodiment]

[0067] A fifth embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the fifth embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 5 to which the fifth embodiment of the information processing device, the information processing method, and the recording medium is applied. [5-1: Configuration of Information Processing Device 5]

[0068] The configuration of the information processing device 5 in the fifth embodiment will be described with reference to Fig. 8. Fig. 8 is a block diagram showing the configuration of the information processing device 5 in the fifth embodiment.

[0069] As shown in FIG. 8 , the information processing device 5 in the fifth embodiment includes a calculation device 21 and a storage device 22, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 4 in the fourth embodiment. Furthermore, the information processing device 5 may include an optical coherence tomography imaging device 100, a communication device 23, an input device 24, and an output device 25, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 4 in the fourth embodiment. However, the information processing device 5 does not necessarily include at least one of the optical coherence tomography imaging device 100, the communication device 23, the input device 24, and the output device 25. The information processing device 5 in the fifth embodiment differs from at least one of the information processing devices 2 in the second embodiment to the information processing device 4 in the fourth embodiment in that the calculation device 21 includes a learning unit 515. Other features of the information processing device 5 may be the same as other features of at least one of the information processing devices 2 in the second embodiment to the information processing device 4 in the fourth embodiment. Therefore, in the following, only the differences from the embodiments already described will be described in detail, and descriptions of other overlapping parts will be omitted as appropriate. [5-2: Learning Operation by Information Processing Device 5]

[0070] The flow of information processing operations performed by the information processing device 5 in the fifth embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the flow of information processing operations performed by the information processing device 5 in the fifth embodiment.

[0071] As shown in FIG. 9 , the acquisition unit 211 acquires three-dimensional luminance data generated by performing optical coherence tomography imaging by irradiating a target with a light beam while two-dimensionally scanning it (step S20). The three-dimensional luminance data includes three-dimensional information for a predetermined number of first positions. The curvature calculation unit 212 calculates curvature information indicating the curvature of the target's surface based on the three-dimensional luminance data (step S21). The first position calculation unit 213 calculates curvilinear coordinates of a predetermined number of first positions on the target's surface based on the curvature information (step S22). The second position calculation unit 2141 calculates curvilinear coordinates of multiple second positions on the target's surface that are different from the predetermined number of first positions based on the curvature information and the curvilinear coordinates of the predetermined number of first positions (step S23). The generation unit 2142 generates a curved surface image indicating the target's surface based on the curvilinear coordinates of the predetermined number of first positions and the curvilinear coordinates of multiple second positions (step S24).

[0072] The learning unit 515 acquires original three-dimensional brightness data including three-dimensional information for more than a predetermined number of original positions, calculates curvature information indicating the curvature of the object's surface based on the three-dimensional brightness data, and calculates curvilinear coordinates of the original positions of the object's surface based on the curvature information, and generates an original curved surface image indicating the object's surface based on the curvilinear coordinates of the original positions (step S50).

[0073] The learning unit 515 compares the curved surface image generated in step S24 with the original curved surface image generated in step S50 (step S51). The learning unit 515 causes the reconstructing unit 214 to learn a curved surface image reconstruction method so that the curved surface image generated based on the three-dimensional data resembles an original curved surface image showing the surface of the object generated based on original three-dimensional data including three-dimensional information for more than a predetermined number of original positions (step S52).

[0074] In other words, the reconstruction unit 214 may learn a method for reconstructing a curved surface image so that a curved surface image generated based on three-dimensional luminance data including three-dimensional information for a predetermined number of first positions is similar to an original curved surface image generated based on original three-dimensional luminance data including three-dimensional information for more than a predetermined number of original positions.

[0075] Furthermore, the learning unit 515 may construct a curved surface image reconstruction model capable of generating a curved surface image similar to the original curved surface image. The curved surface image reconstruction model may be a model that outputs a curved surface image when curvature information and curved surface coordinates of a plurality of first positions are input. The reconstructing unit 214 may generate a curved surface image using the curved surface image reconstruction model. By using the trained curved surface image reconstruction model, the reconstructing unit 214 can generate a highly accurate curved surface image similar to the original curved surface image.

[0076] The parameters that define the operation of the curved image reconstruction model may be stored in the storage device 22. The parameters that define the operation of the curved image reconstruction model may be parameters that are updated by a learning operation, such as weights and biases of a neural network. [5-3: Technical Effects of the Information Processing Device 5]

[0077] The information processing device 5 in the fifth embodiment causes the reconstructing unit 214 to learn a method for reconstructing a curved surface image so that the curved surface image resembles an original curved surface image generated based on original three-dimensional data including three-dimensional information of original positions. Therefore, the reconstructing unit 214 can generate a highly accurate curved surface image of the object based on three-dimensional data including three-dimensional information of a predetermined number of first positions. [6: Sixth Embodiment]

[0078] A sixth embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the sixth embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 6 to which the sixth embodiment of the information processing device, the information processing method, and the recording medium is applied. [6-1: Configuration of Information Processing Device 6]

[0079] The configuration of the information processing device 6 in the sixth embodiment will be described with reference to Fig. 10. Fig. 10 is a block diagram showing the configuration of the information processing device 6 in the sixth embodiment.

[0080] As shown in FIG. 10 , the information processing device 6 in the sixth embodiment includes a calculation device 21 and a storage device 22, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 5 in the fifth embodiment. Furthermore, the information processing device 6 may include an optical coherence tomography imaging device 100, a communication device 23, an input device 24, and an output device 25, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 5 in the fifth embodiment. However, the information processing device 6 does not necessarily include at least one of the optical coherence tomography imaging device 100, the communication device 23, the input device 24, and the output device 25. The information processing device 6 in the sixth embodiment differs from at least one of the information processing devices 2 in the second embodiment to the information processing device 5 in the fifth embodiment in that the calculation device 21 includes a correspondence unit 616 and a matching unit 617. Other features of the information processing device 6 may be the same as other features of at least one of the information processing devices 2 in the second embodiment to the information processing device 5 in the fifth embodiment. Therefore, in the following, only the differences from the embodiments already described will be described in detail, and the description of other overlapping parts will be omitted as appropriate. [6-2: Information Processing Operation by Information Processing Device 6]

[0081] The flow of information processing operations performed by the information processing device 6 in the sixth embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the flow of information operations performed by the information processing device 6 in the sixth embodiment.

[0082] As shown in FIG. 11 , the acquisition unit 211 acquires three-dimensional luminance data generated by performing optical coherence tomography imaging by irradiating a light beam onto an object while scanning it two-dimensionally (step S20). The curvature calculation unit 212 calculates curvature information indicating the curvature of the object's surface based on the three-dimensional luminance data (step S21). The first position calculation unit 213 calculates curvilinear coordinates of multiple first positions on the object's surface based on the curvature information (step S22). The second position calculation unit 2141 calculates curvilinear coordinates of multiple second positions on the object's surface that are different from the multiple first positions based on the curvature information and the curvilinear coordinates of the multiple first positions (step S23). The generation unit 2142 generates a curved surface image indicating the object's surface based on the curvilinear coordinates of the multiple first positions and the curvilinear coordinates of the multiple second positions (step S24).

[0083] The association unit 616 extracts feature points included in the curved surface image. For example, if the curved surface image is a pattern image showing a skin pattern, the feature points of the pattern image may include "end points" where the pattern ends and "branch points" where the pattern branches. If a feature point included in the curved surface image is located in an area based on the second position, the association unit 616 associates the feature point with second position information indicating that the feature point is based on the second position (step S60).

[0084] The feature points of the pattern image may be positions that can capture the features of the pattern image well. For example, they may be positions that are used to compare the two pattern images when matching them. Therefore, it is often preferable to adopt more reliable locations as positions that can capture the features of the pattern image well. It is often preferable to be able to distinguish from which area the positions extracted as feature points originate, i.e., whether they originate from an area other than the area based on the second position or from the area based on the second position. The information processing device 6 in the sixth embodiment can distinguish whether they originate from an area other than the area based on the second position or from the area based on the second position.

[0085] The matching unit 617 reduces the weighting of the feature points associated with the second position information (step S61).

[0086] The comparison unit 617 compares the curved surface image with a registered curved surface image that has been registered in advance (step S62). [6-3: Technical Effects of the Information Processing Device 6]

[0087] The information processing device 6 in the sixth embodiment associates the feature point with second position information indicating that the feature point is based on the second position, and can determine whether or not to use the corresponding position as a feature point for processing depending on the application. In particular, when matching pattern images with each other, information that can determine whether or not the feature point can be used for matching is useful. [7: Seventh Embodiment]

[0088] A seventh embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the seventh embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 7 to which the seventh embodiment of the information processing device, the information processing method, and the recording medium is applied. [7-1: Configuration of Information Processing Device 7]

[0089] The configuration of the information processing device 7 in the seventh embodiment will be described with reference to Fig. 12. Fig. 12 is a block diagram showing the configuration of the information processing device 7 in the seventh embodiment.

[0090] As shown in FIG. 12 , the information processing device 7 in the seventh embodiment includes a calculation device 21 and a storage device 22, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 6 in the sixth embodiment. Furthermore, the information processing device 7 may include an optical coherence tomography imaging device 100, a communication device 23, an input device 24, and an output device 25, similar to at least one of the information processing devices 2 in the second embodiment to the information processing device 6 in the sixth embodiment. However, the information processing device 7 does not necessarily include at least one of the optical coherence tomography imaging device 100, the communication device 23, the input device 24, and the output device 25. The information processing device 7 in the seventh embodiment differs from at least one of the information processing devices 2 in the second embodiment to the information processing device 6 in the sixth embodiment in that the calculation device 21 includes a control unit 718. Other features of the information processing device 7 may be the same as other features of at least one of the information processing devices 2 in the second embodiment to the information processing device 6 in the sixth embodiment. Therefore, in the following, only the differences from the embodiments already described will be described in detail, and the description of other overlapping parts will be omitted as appropriate. [7-2: Control operation of the optical coherence tomography imaging device 100 by the information processing device 7]

[0091] The flow of the control operation of the optical coherence tomography imaging apparatus 100 performed by the information processing device 7 in the seventh embodiment will be described with reference to Fig. 13. Fig. 13 is a flowchart showing the flow of the control operation of the optical coherence tomography imaging apparatus 100 performed by the information processing device 7 in the seventh embodiment.

[0092] 13 , the acquisition unit 211 acquires three-dimensional luminance data generated by performing optical coherence tomography imaging by irradiating a target with a light beam while performing two-dimensional scanning (step S70). In the optical coherence tomography imaging for generating the three-dimensional luminance data acquired in step S70, the number of irradiation positions of the object light by the optical coherence tomography imaging device 100 may be less than the number of the first positions. For example, the number of irradiation positions of the object light may be half or less of the number of the first positions.

[0093] The curvature calculation unit 212 calculates curvature information indicating the curvature of the surface of the object based on the three-dimensional luminance data acquired in step S70 (step S71).

[0094] Based on the curvature information calculated in step S71, the control unit 718 determines a scanning speed at which the scanner unit of the optical coherence tomography imaging apparatus 100 moves the light irradiation position relatively (step S72). The control unit 718 may, for example, divide the region corresponding to the region imaged by optical coherence tomography into a predetermined number of microregions and calculate the curvature information for each microregion. In this case, the control unit 718 may determine a scanning speed at which the scanner unit of the optical coherence tomography imaging apparatus 100 moves the light irradiation position relatively for each microregion.

[0095] The control unit 718 controls the scanning of each microscopic region with light by moving the scanner unit of the optical coherence tomography imaging apparatus 100 relative to the microscopic region at the speed determined in step S72 (step S73). The control unit 718 may control the optical coherence tomography scanning by the scanner unit of the optical coherence tomography imaging apparatus 100.

[0096] In step S20 in each of the above embodiments, three-dimensional luminance data generated by performing optical coherence tomography imaging in step S73 may be acquired.

[0097] For example, if the target is a finger, the curvature often increases with distance from the center of the imaging area compared to the center. Since resolution tends to decrease in areas with large curvature, it is preferable to obtain more detailed information. Scanning the target at a slower speed can obtain information on the target at finer intervals compared to scanning the target at a faster speed. Therefore, the control unit 718 may move the target at a slower speed relative to areas farther from the center of the imaging area compared to areas at the center of the imaging area. As a result, the three-dimensional data is generated such that the density of the multiple first positions increases with distance from the center of the area where the multiple first positions exist.

[0098] The information processing device 7 in the seventh embodiment may include a stereoscopic image generating device, or may transmit and receive information to and from the stereoscopic image generating device via the communication device 23. The stereoscopic image generating device may generate a stereoscopic image of the object, or may generate a stereoscopic image of the object including at least an area from which three-dimensional luminance data is acquired. In this case, the control unit 718 may measure the curvature of each minute area based on the stereoscopic image, and the control unit 718 may determine the scanning speed at which the scanner unit of the optical coherence tomography imaging device 100 relatively moves the light irradiation position based on the curvature of each minute area. [7-3: Technical Effects of the Information Processing Device 7]

[0099] The information processing device 7 in the seventh embodiment can obtain information on objects at smaller intervals as the curvature of the area increases.

[0100] In each of the above-described embodiments, the object is a hand, but the object is not limited to a hand. Each of the above-described embodiments can be applied to objects other than a hand. For example, the object may be skin of a body other than a hand, an iris, fruit, etc. The skin of a body other than a hand may be, for example, skin of a foot. When optical coherence tomography imaging of the skin of a hand or a foot is performed, light that penetrates a resin or the like may be used. Since the iris is a muscle fiber, iris feature amounts can be obtained from optical coherence tomography images. Each of the above-described embodiments may be used in situations where it is preferable to non-invasively measure the surface and near-surface conditions of the skin, iris, fruit, etc. of the body. [8: Supplementary Note]

[0101] The following supplementary notes are further disclosed with respect to the above-described embodiments. [Supplementary Note 1] An information processing device comprising: an acquisition means for acquiring three-dimensional data of an object; a curvature calculation means for calculating curvature information indicating a curvature of a surface of the object based on the three-dimensional data; a first position calculation means for calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information; a second position calculation means for calculating curvilinear coordinates of a plurality of second positions on the surface of the object different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions; and a generation means for generating a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions. [Supplementary Note 2] The information processing device according to Supplementary Note 1, wherein the three-dimensional data is three-dimensional brightness data generated by performing optical coherence tomography imaging by irradiating the object with a light beam while scanning it two-dimensionally. [Supplementary Note 3] The information processing device according to Supplementary Note 1 or 2, wherein the second position calculation means calculates more curvilinear coordinates of the second positions based on the curvature information and the curvilinear coordinates of the plurality of first positions for areas with greater curvature on the surface of the object. [Supplementary Note 4] The information processing device according to Supplementary Note 1 or 2, wherein the reconstruction means generates the curved surface image by applying compressed sensing. [Supplementary Note 5] The information processing device according to Supplementary Note 1 or 2, wherein the three-dimensional data includes three-dimensional information for a predetermined number of the first positions, and further comprises learning means for causing the reconstruction means to learn a reconstruction method for the curved surface image so that the curved surface image generated based on the three-dimensional data resembles an original curved surface image showing the surface of the object generated based on original three-dimensional data including three-dimensional information for more original positions than the predetermined number. [Supplementary Note 6] The information processing device according to Supplementary Note 1 or 2, further comprising: a matching means for matching, when a feature point included in the curved surface image exists in an area based on the second position, second position information indicating that the feature point is based on the second position, with the feature point; and a matching means for matching the curved surface image with a registered curved surface image that has been registered in advance, wherein the matching means reduces a weighting of the feature point with which the second position information is associated.[Supplementary Note 7] The information processing device according to Supplementary Note 1 or 2, wherein the three-dimensional data is generated such that the density of the plurality of first positions increases with distance from a center of an area in which the plurality of first positions exist. [Supplementary Note 8] An information processing method comprising: acquiring three-dimensional data of an object; calculating curvature information indicating a curvature of a surface of the object based on the three-dimensional data; calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information; calculating curvilinear coordinates of a plurality of second positions on the surface of the object different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions; and generating a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions. [Supplementary Note 9] A recording medium having recorded thereon a computer program for causing a computer to execute an information processing method of: acquiring three-dimensional data of an object; calculating curvature information indicating the curvature of the surface of the object based on the three-dimensional data; calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information; calculating curvilinear coordinates of a plurality of second positions on the surface of the object different from the plurality of first positions based on the curvature information and the curvilinear coordinates of the plurality of first positions; and generating a curved surface image indicating the surface of the object based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.

[0102] At least some of the components of each of the above-described embodiments can be appropriately combined with at least some of the other components of each of the above-described embodiments. Some of the components of each of the above-described embodiments may not be used.

[0103] This disclosure is not limited to the above-described embodiments. This disclosure may be modified as appropriate within the scope of the claims and the technical idea that can be read from the entire specification. Information processing devices, information processing methods, and recording media incorporating such modifications are also included in the technical idea of ​​this disclosure. Furthermore, to the extent permitted by law, all publications and papers described in this specification are incorporated herein by reference.

[0104] To the extent permitted by law, this application claims priority to Japanese Patent Application No. 2022-096468, filed June 15, 2022, the disclosure of which is incorporated herein in its entirety by reference.

[0105] 1, 2, 3, 4, 5, 6, 7 Information processing device 100 Optical coherence tomography imaging device 11, 211 Acquisition unit 12, 212 Curvature calculation unit 13, 213 First position calculation unit 14, 214 Reconstruction unit 141, 2141 Second position calculation unit 142, 2142 Generation unit 515 Learning unit 616 Correspondence unit 617 Matching unit 718 Control unit

Claims

1. An acquisition means for acquiring three-dimensional data of an object; a curvature calculation means for calculating curvature information indicating a curvature of a surface of the object based on the three-dimensional data; a first position calculation means for calculating curvilinear coordinates of a plurality of first positions on the surface of the object based on the curvature information; a second position calculation means for calculating curvilinear coordinates of a plurality of second positions on the surface of the object, the second positions being different from the plurality of first positions, based on the curvature information and the curvilinear coordinates of the plurality of first positions, and a generation means for generating a curved surface image showing the surface of the object, based on the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions; An information processing device comprising:

2. The three-dimensional data is three-dimensional brightness data generated by performing optical coherence tomography imaging by irradiating the object with a light beam while scanning it in two dimensions. The information processing device according to claim 1 .

3. The second position calculation means calculates the curvilinear coordinates of the second positions more in an area having a larger curvature on the surface of the object based on the curvature information and the curvilinear coordinates of the plurality of first positions.

3. The information processing device according to claim 1 or 2.

4. The reconstruction means applies compressed sensing to generate the curved surface image.

3. The information processing device according to claim 1 or 2.

5. The three-dimensional data includes three-dimensional information of a predetermined number of the first positions, The present invention further includes a learning means for causing the reconstructing means to learn a method for reconstructing the curved surface image so that the curved surface image generated based on the three-dimensional data resembles an original curved surface image showing the surface of the object generated based on original three-dimensional data including three-dimensional information of original positions that is more than the predetermined number.

3. The information processing device according to claim 1 or 2.

6. a correspondence association means for associating, when a feature point included in the curved surface image exists in a region based on the second position, second position information indicating that the feature point is based on the second position, with the feature point; A matching means for matching the curved surface image with a registered curved surface image that has been registered in advance; Further comprising: The matching means reduces a weighting of the feature point to which the second position information corresponds.

3. The information processing device according to claim 1 or 2.

7. The three-dimensional data is generated such that the density of the first positions increases as the distance from the center of the area in which the first positions exist increases.

3. The information processing device according to claim 1 or 2.

8. Acquire three-dimensional data of the target, calculating curvature information indicative of a curvature of a surface of the object based on the three-dimensional data; calculating curvilinear coordinates of a plurality of first locations on a surface of the object based on the curvature information; calculating curvilinear coordinates of a plurality of second locations on a surface of the object that are different from the plurality of first locations based on the curvature information and the curvilinear coordinates of the plurality of first locations; generating a curved image representing a surface of the object based on the curvilinear coordinates of the first positions and the curvilinear coordinates of the second positions; A computer implemented information processing method.

9. On the computer, Acquire three-dimensional data of the target, calculating curvature information indicative of a curvature of a surface of the object based on the three-dimensional data; calculating curvilinear coordinates of a plurality of first locations on a surface of the object based on the curvature information; calculating curvilinear coordinates of a plurality of second locations on a surface of the object that are different from the plurality of first locations based on the curvature information and the curvilinear coordinates of the plurality of first locations; generating a curved image representing a surface of the object based on the curvilinear coordinates of the first positions and the curvilinear coordinates of the second positions; A computer program for executing an information processing method.