Image analysis system, image analysis method, and image analysis program

Abstract

To easily estimate data including an image excluding the influence of aliasing components.SOLUTION: An image analysis system comprises: a preprocessing unit for subjecting image data to antialiasing; a Fourier transformation unit in which the image data subjected to the antialiasing are Fourier-transformed to create a transformed image including a Fourier image obtained by the transformation; and a calculation unit in which intensity information included in the Fourier image of the transformed image after the Fourier transformation is integrated in any direction to calculate spectral data.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to an image analysis system, an image analysis method, and an image analysis program.

Background Art

[0002] In image data, since it is not possible to draw more finely than in pixel units, jaggedness, that is, aliasing, occurs around an object.

[0003] Patent Document 1 discloses a technique related to a correction method for eliminating the influence of aliasing in a power spectrum.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In order to estimate data of an image that does not include an aliasing component, data with different sample intervals is required. However, with a general observation method, it is difficult to obtain data with different sample intervals, and it has been difficult to actually implement.

[0006] An object of the present disclosure is to provide an image analysis system, an image analysis method, and an image analysis program that can easily estimate data including an image excluding the influence of an aliasing component.

Means for Solving the Problems

[0007] As described in claim 1 The image analysis system captured images of the material particles. For the image data Regarding the brightness gradient between the aforementioned particles and the background A preprocessing unit that performs antialiasing processing, and Fourier-transforms the antialiased image data, and the The intensity distribution is isotropic.A Fourier transform unit creates a transformed image that includes a Fourier image, and integrates the intensity information contained in the Fourier image of the transformed image with respect to an arbitrary direction. The aforementioned particles Calculate spectral data Then, the EM algorithm analysis method is applied to the calculated spectral data to calculate the size distribution of the azimuth. It comprises a calculation unit and

[0008] The image analysis system described in claim 1 calculates spectral data using anti-aliased image data. This enables analysis of orientation using spectral data from which the influence of aliasing components has been removed. Furthermore, it is possible to analyze direction by removing the effects of aliasing components.

[0010] Claim 2 The image analysis method described is Images of the material particles. Image data Regarding the brightness gradient between the aforementioned particles and the background Anti-aliasing is performed, and the anti-aliased image data is subjected to a Fourier transform, and the result obtained by the transform The intensity distribution is isotropic. A transformed image including the Fourier image is created, and the intensity information contained in the Fourier image of the transformed image after the Fourier transform is integrated with respect to an arbitrary direction. The aforementioned particles Calculate spectral data Then, the EM algorithm analysis method is applied to the calculated spectral data to calculate the size distribution of the azimuth. The computer then performs the processing.

[0011] Claim 3 The image analysis program described below is Images of the material particles. Image data Regarding the brightness gradient between the aforementioned particles and the background Anti-aliasing is performed, and the anti-aliased image data is subjected to a Fourier transform, and the result obtained by the transform The intensity distribution is isotropic. A transformed image including the Fourier image is created, and the intensity information contained in the Fourier image of the transformed image after the Fourier transform is integrated with respect to an arbitrary direction. The aforementioned particles Calculate spectral data Then, the EM algorithm analysis method is applied to the calculated spectral data to calculate the size distribution of the azimuth. The computer then performs the process. [Effects of the Invention]

[0012] According to the technology disclosed herein, data including images with the effects of aliasing components removed can be easily estimated. [Brief explanation of the drawing]

[0013] [Figure 1] FIG. 1 is a diagram showing an example when image data including aliasing is subjected to Fourier transform. [Figure 2] FIG. 2 is a diagram showing an example when anti-aliased image data is subjected to Fourier transform. [Figure 3] FIG. 3 is an example of improvement by anti-aliasing processing. [Figure 4] FIG. 4 is a diagram showing a functional configuration of an image analysis system. [Figure 5] FIG. 5 is a block diagram showing a hardware configuration of an image analysis apparatus. [Figure 6] FIG. 6 is a flowchart showing a flow of image analysis processing as an image analysis method executed by the image analysis apparatus of the present embodiment.

MODE FOR CARRYING OUT THE INVENTION

[0014] The outline of an embodiment of the present invention will be described. When expressing the characteristics of a material structure, Fourier transform of image data typified by a microscopic image is often performed. An image obtained by subjecting image data to Fourier transform, that is, a Fourier image, includes information on a periodic structure included in the material structure. Therefore, by analyzing only information in a specific direction, the periodic structure in that direction can be analyzed and utilized.

[0015] However, when Fourier-transforming image data containing aliasing around an object, a Fourier image containing peripheral information with the influence of aliasing remaining will be obtained. Since the periodic information in the Fourier image containing aliasing is inaccurate, the resulting tissue information will also be inaccurate. Therefore, in image data where the size of the object relative to the pixels is not sufficiently large, the analysis of peripheral information in a specific orientation could not be performed adequately. Also, as described above in the problems, there are issues in data acquisition when attempting to correct aliasing. In the following description, the "particles" contained in the image data are synonymous with the above-mentioned "objects", and it is merely a distinction for convenience of explanation.

[0016] FIG. 1 is a diagram showing an example when Fourier-transforming image data containing aliasing. D1 is image data with a circular particle arranged in the center. The lower right frame of D1 is an enlarged central particle, and it can be seen that when the size of the particle is small relative to the image size, the shape of the particle cannot be smoothly represented. F1 is the transformed image obtained by Fourier-transforming the image data of D1. When Fourier-transforming an image containing a circular particle, an isotropic intensity distribution should be obtained, but it can be seen that in the transformed image of F1, the originally isotropic intensity information is distorted. F2 shows specific orientations a1 and a2 that are the analysis targets of the transformed image of F1. It can be seen that the intensity is different within the ranges of a1 and a2 where the same intensity distribution should be present, and an error that does not originally exist has occurred. Thus, when attempting to analyze a specific orientation, it may not be correctly evaluated due to the influence of aliasing.

[0017] Therefore, in this embodiment, processing is performed to obtain information about the periodic structure generated by the object, including the particle size distribution, for each orientation in the image data. In the preprocessing, the brightness difference between the object and the background is smoothed out by anti-aliasing of the image data. In the calculation process, the power spectrum is obtained by integrating the intensity information of the Fourier image obtained by performing a Fourier transform on the anti-aliased image data. For the power spectrum, a one-dimensional power spectrum is obtained for the required orientation. From the power spectrum, the size distribution for each orientation can be determined using the EM algorithm or the like.

[0018] Figure 2 shows an example of the Fourier transform applied to anti-aliased image data. By applying anti-aliasing to the image data D1, the anti-aliased image data D1a is obtained. The image data D1a shows a smooth representation of the particle shape. F1' is the transformed image obtained by Fourier transforming D1a. It can be seen that the Fourier image of the transformed image F1' is an isotropic image. The function used for anti-aliasing is one that smoothly connects the brightness gradient between the particles and the background at the subpixel level.

[0019] Figure 3 shows an example of improvement through anti-aliasing. The graph in Figure 3 shows the intensity distribution with brightness on the vertical axis and a predetermined direction on the horizontal axis. s1 is the brightness of the image data before improvement, and s2 is the brightness of the image data after improvement. The brightness of s1 is binary. By applying anti-aliasing to s1 before improvement, the brightness gradient can be smoothed out as shown in s2.

[0020] Figure 4 shows the functional configuration of the image analysis system 100. As shown in Figure 4, in the image analysis system 100, the user terminal 102 and the image analysis device 110 are connected via a network N such as the Internet.

[0021] The user terminal 102 is a terminal that performs input related to image analysis. The user terminal 102 is composed of a control unit 104 and a display unit 106, and has an interface that allows selection and specification of images stored in the storage unit 112 of the image analysis device 110. The control unit 104 of the user terminal 102 receives the specification of the image data to be processed and the specification of the direction to be analyzed for said image data, and transmits it to the image analysis device 110. The user terminal 102 also receives the images processed by the image analysis device 110 and displays them on the display unit 106. Note that the user terminal 102 may be configured as an integrated unit with the image analysis device 110.

[0022] Figure 5 is a block diagram showing the hardware configuration of the image analysis device 110. As shown in Figure 5, the image analysis device 110 has a CPU (Central Processing Unit) 11, ROM (Read Only Memory) 12, RAM (Random Access Memory) 13, storage 14, input unit 15, display unit 16, and communication interface (I / F) 17. Each component is connected to the others via a bus 19 so that they can communicate with each other. The user terminal 102 may have a similar hardware configuration.

[0023] The CPU 11 is a central processing unit that executes various programs and controls various components. Specifically, the CPU 11 reads a program from the ROM 12 or storage 14 and executes the program using the RAM 13 as a working area. The CPU 11 controls each of the above components and performs various calculations according to the program stored in the ROM 12 or storage 14. In this embodiment, an image analysis program is stored in the ROM 12 or storage 14.

[0024] ROM12 stores various programs and data. RAM13 temporarily stores programs or data as a working area. Storage14 consists of a storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs, including the operating system, and various data.

[0025] The input unit 15 includes a pointing device such as a mouse and a keyboard, and is used for various types of input.

[0026] The display unit 16 is, for example, a liquid crystal display and displays various information. The display unit 16 may also function as an input unit 15 by employing a touch panel system.

[0027] The communication interface 17 is an interface for communicating with other devices such as terminals. For such communication, a wired communication standard such as Ethernet® or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi® may be used.

[0028] The functional configuration of the image analysis device 110 shown in Figure 4 will now be explained. Functionally, the image analysis device 110 consists of a storage unit 112, a preprocessing unit 120, a Fourier transform unit 122, and a calculation unit 124. Each functional configuration is realized by the CPU 11 reading an image analysis program stored in the ROM 12 or storage 14, expanding it into the RAM 13, and executing it. The image analysis device 110 receives the specification of image data and the orientation to be analyzed from the user terminal 102 and executes the processing of each unit. The image analysis device 110 transmits the processed spectral data and particle size distribution of the image data to the user terminal 102.

[0029] Multiple image data are pre-stored in the memory unit 112. The image data is, for example, an image of a material, or a digital image showing particles.

[0030] The preprocessing unit 120 performs anti-aliasing on the image data specified by the user terminal 102. The preprocessing unit 120 outputs the anti-aliased image data to the Fourier transform unit 122. Any function that can perform smoothing without significantly changing the size or shape of the object can be used for the anti-aliasing process.

[0031] The Fourier transform unit 122 performs a Fourier transform on the anti-aliased image data to create a transformed image. The transformed image includes the Fourier image obtained by the transformation. The Fourier transform unit 122 outputs the transformed image to the calculation unit 124.

[0032] The calculation unit 124 calculates spectral data by integrating the intensity information contained in the Fourier image of the transformed image after the Fourier transform over an arbitrary direction. For example, the calculation unit 124 assumes that the direction is the direction specified by the user terminal 102. A predetermined range is set for the specified direction, and one-dimensional spectral data is obtained by integrating the intensity within that range in the circumferential direction. The calculation unit 124 also applies a predetermined analysis method, such as the EM algorithm, to the calculated spectral data to calculate the size distribution over the arbitrary direction.

[0033] (Control flow) Figure 6 is a flowchart showing the flow of the image analysis process as an image analysis method performed by the image analysis device 110 of this embodiment.

[0034] In step S100, the CPU 11 performs anti-aliasing on the specified image data.

[0035] In step S102, the CPU 11 performs a Fourier transform on the anti-aliased image data to create a transformed image.

[0036] In step S104, the CPU 11 calculates spectral data by integrating the intensity information contained in the Fourier image of the transformed image after the Fourier transform over an arbitrary direction.

[0037] In step S106, the CPU 11 applies a predetermined analysis method, such as the EM algorithm, to the calculated spectral data to calculate the size distribution for an arbitrary direction.

[0038] In step S106, the CPU 11 outputs the calculated spectral data and size distribution as analysis results to the user terminal 102.

[0039] As described above, the image analysis system 100 of this embodiment can easily estimate data including images with the effects of aliasing components removed.

[0040] In addition, the various processes that the CPU 11 reads and executes in the above embodiment may be executed by various processors other than the CPU. Examples of such processors include PLDs (Programmable Logic Devices) such as FPGAs (Field-Programmable Gate Arrays) whose circuit configuration can be changed after manufacturing, GPUs (Graphics Processing Units), and ASICs (Application Specific Integrated Circuits), which are dedicated electrical circuits that have a circuit configuration specifically designed to execute a particular process. Furthermore, each of the above processes may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (for example, multiple FPGAs, and a combination of a CPU and an FPGA). More specifically, the hardware structure of these various processors is an electrical circuit that combines circuit elements such as semiconductor elements.

[0041] Furthermore, in the above embodiment, the information processing program was described as being pre-stored (installed) on a computer-readable non-temporary recording medium. For example, the information processing program is pre-stored in ROM 12 or storage 14. However, it is not limited to this, and each program may be provided in a form recorded on a non-temporary recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disc Read Only Memory), or USB (Universal Serial Bus) memory. Also, the image analysis program may be provided in a form downloaded from an external device via a network.

[0042] The processing flow described in the above embodiment is just one example, and unnecessary steps may be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. [Explanation of Symbols]

[0043] 100 Image Analysis Systems 102 User terminals 104 Control Unit 106 Display section 110 Image analysis device 112 Storage section 120 Pre-processing 122 Fourier Transform Section 124 Calculation Department

Claims

1. A preprocessing unit that performs anti-aliasing on the brightness gradient between the particles and the background in image data that captures the particles of a material, A Fourier transform unit performs a Fourier transform on the anti-aliased image data to create a transformed image that includes a Fourier image with an isotropic intensity distribution obtained by the transformation. A calculation unit that calculates the spectral data of the particles by integrating the intensity information contained in the Fourier image of the transformed image after the Fourier transform over an arbitrary direction, and then applies the analysis method of the EM algorithm to the calculated spectral data to calculate the size distribution of the direction, An image analysis system equipped with the following features.

2. Anti-aliasing is performed on the brightness gradient between the particles and the background in image data that captures the particles of the material, The anti-aliased image data is subjected to a Fourier transform to create a transformed image that includes a Fourier image with an isotropic intensity distribution obtained by the transform. The spectral data of the particle is calculated by integrating the intensity information contained in the Fourier image of the transformed image after the Fourier transform over an arbitrary direction, and the size distribution of the direction is calculated by applying the analysis method of the EM algorithm to the calculated spectral data. An image analysis method in which a computer performs the processing.

3. Anti-aliasing is performed on the brightness gradient between the particles and the background in image data that captures the particles of the material, The anti-aliased image data is subjected to a Fourier transform to create a transformed image that includes a Fourier image with an isotropic intensity distribution obtained by the transform. The spectral data of the particle is calculated by integrating the intensity information contained in the Fourier image of the transformed image after the Fourier transform over an arbitrary direction, and the size distribution of the direction is calculated by applying the analysis method of the EM algorithm to the calculated spectral data. An image analysis program that has a computer perform the processing.

Images