A white light interferometer utilizing synusoid interpolation, and the synusoid interpolation method for the white light interferometer.

Abstract

A white light interferometer utilizing a synusoid interpolation method that can naturally represent interference fringes generated by measured light and reflected light, and a synusoid interpolation method for the white light interferometer are disclosed. The white light interferometer utilizing the synusoid interpolation method comprises a CCD image sensor (Charge_Coupled_Device_image_sensor) that generates multiple interference fringe images by capturing interference fringes, and an image analysis processor that generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) by accumulating multiple interference fringe images.

Description

[Technical Field]

[0001] The present invention relates to a white light interferometer utilizing sinusoidal interpolation, and a method for sinusoidal interpolation of the white light interferometer. More specifically, the present invention relates to a white light interferometer and a method for sinusoidal interpolation of the white light interferometer, which utilize a sinusoidal interpolation method in which, after white light is irradiated onto a sample and a mirror, the reflected measurement light and the interference fringes generated by the reflected light are interpolated through the sinusoidal interpolation method. [Background technology]

[0002] In recent years, there has been a growing demand in the fields of nanoscience, semiconductors, nanophysics, nanochemistry, nanomaterials, nanooptics, surface science, medical imaging, biology, biophysics, medical physics, and medical optics to measure the three-dimensional shape information of samples that have three-dimensional nanostructures or micrometer structures.

[0003] To measure the three-dimensional shape information of a sample in this way, white light interferometers, which utilize the interference phenomenon of white light, have been used.

[0004] A typical white light interferometer utilizes a beam splitter that separates the white light source, creating separate paths for the sample and the mirror. After the white light is reflected from the sample and the mirror by the beam splitter, it is combined and transmitted to a CCD image sensor. The CCD image sensor captures an interference fringe image formed by the combined reflected light from the sample and the mirror. An image analysis processor analyzes the interference fringe image captured by the CCD image sensor to generate three-dimensional shape information of the sample.

[0005] In this process, the sample is placed on a stage, which is moved along the path axis (generally the Z-axis) of the light source by a separate drive assembly, thereby generating a path difference between the sample side and the mirror side. The interference fringe images captured by the CCD image sensor form different interference fringe images due to the change in the path difference between the sample side and the mirror side. The image analysis processor generates three-dimensional shape information of the sample based on the interference fringes, which are the cumulative effect of these different interference fringe images.

[0006] On the other hand, conventional white light interferometers have a problem in that the shape of the white light interference fringes (WLI_Fringe) is unnaturally represented by the physically limited minimum movable length, i.e., Z_Step_Size, of the drive assembly that moves the stage to generate a path difference between the sample side and the mirror side.

[0007] The problem of unnatural shapes in white light interference fringes (WLI_Fringe) due to such restrictive Z_Step_Sizes has been solved by interpolation using spline interpolation (Cubic_Spline). However, spline interpolation has the drawback of being computationally intensive while having low accuracy. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2015-078879 [Overview of the project] [Problems that the invention aims to solve]

[0009] The objective of the present invention to solve the above-mentioned problems is to provide a white light interferometer that utilizes a synusoid interpolation method and a synusoid interpolation method for a white light interferometer, which can naturally represent the shape of interference fringes by interpolating the reflected measurement light and the interference fringes generated by the reflected light after the white light split by the beam splitter is irradiated onto the sample and the mirror respectively, using a synusoid interpolation method.

[0010] Another object of the present invention is to provide a white light interferometer that utilizes a synusoid interpolation method, which can provide a fast and accurate interpolation method by utilizing the mathematical conditions of the synusoid wavelength, and a synusoid interpolation method for the white light interferometer. [Means for solving the problem]

[0011] To achieve the above-mentioned objectives, a white light interferometer utilizing a synusoid interpolation method according to one embodiment of the present invention comprises a light source that provides white light, a stage on which a sample is placed, a stage moving assembly that moves the stage in the axis direction of the white light path, a mirror having a reflective surface, a beam splitter that divides the path of white light provided by the light source into the sample side and the mirror side, a CCD image sensor (Charge_Coupled_Device_image_sensor) that receives measurement light reflected from the sample and reflected light reflected from the mirror from the beam splitter while the stage is moving in the axis direction of the path by the stage moving assembly, and generates multiple interference fringe images by capturing the interference fringes generated by the measurement light and the reflected light, and an image analysis processor that generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) by accumulating the multiple interference fringe images. The image analysis processor generates an interpolated white light interference fringe signal (I[n]′) by interpolating the generated white light interference fringe signal (I[n]) through sinusoidal interpolation.

[0012] The image analysis processor interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method. It generates an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]) by dividing the white light interference fringe signal (I[n]) into amplitude and phase components, respectively, and generates an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through the synusoid interpolation method. Furthermore, it generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]').

[0013] The image analysis processor generates an amplitude graph and a phase graph by dividing the white light interference fringe signal into amplitude and phase components, respectively. Based on the following <Equation 1>, it generates the amplitude graph (Envelope) by extracting the amplitude component (A[n]) from the white light interference fringe signal (I[n]) and generates the phase graph (Phase) by extracting the phase component (θ[n]) from the white light interference fringe signal (I[n]).

[0014] A[n](Envelope)=(c[n] 2 +s[n] 2 ) 1 / 2 . θ[n](Phase)=Atan(s[n],c[n]). <Formula 1> (Here, A[n] is the amplitude (Amplitude_on_Pixel_of_WLI_Fringe) of the pixels of the white light interference fringe signal. θ[n] is the phase (Phase_on_Pixel_of_WLI_Fringe) of the pixels of the white light interference fringe signal. c[n] is the cosine component (Cosine_Component_of_WLI_Fringe) of the white light interference fringe signal, which is calculated as c[n]=A[n]×cos(θ[n]). s[n] is the sine component (Sine_Component_of_WLI_Fringe) of the white light interference fringe signal, which is calculated as s[n]=A[n]×sin(θ[n]).)

[0015] When the image analysis processor generates an interpolated amplitude graph (A[n]′) and an interpolated phase graph (θ[n]′) by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) through the sine interpolation method respectively, it calculates the interpolation values (A[n + 0.5], θ[n + 0.5]) between the first measurement values (A[n], θ[n]) and the second measurement values (A[n+1], θ[n+1]) of each of the amplitude graph (A[n]) and the phase graph (θ[n]) based on the following <Equation 2>.

[0016] A[n + 0.5]=0.5*(A[n]+A[n+1]). θ[n + 0.5]=0.5*(θ[n]+θ[n+1]). <Equation 2> (Here, A[n] is the amplitude (Amplitude_on_Pixel_of_WLI_Fringe) of the pixels of the white light interference fringe signal. θ[n] is the phase (Phase_on_Pixel_of_WLI_Fringe) of the pixels of the white light interference fringe signal.)

[0017] When generating the interpolated white light interference fringe signal (I[n]′) based on the interpolated amplitude graph (A[n]′) and the interpolated phase graph (θ[n]′), the image analysis processor generates the interpolated white light interference fringe signal (I[n]′) based on the measured values (A[n], θ[n]) of each of the amplitude graph (A[n]) and the phase graph (θ[n]), and the interpolated values (A[n + 0.5], θ[n + 0.5]) of each of the interpolated amplitude graph (A[n]′) and the interpolated phase graph (θ[n]′), according to the following <Equation 3>.

[0018] I[n]=A[n]×cos(θ[n]). <Equation 3> (Here, the A[n] is the amplitude (Amplitude_on_Pixel_of_WLI_Fringe) of the pixel of the white light interference fringe signal. The θ[n] is the phase (Phase_on_Pixel_of_WLI_Fringe) of the pixel of the white light interference fringe signal).

[0019] To achieve the above object, a white light interferometer utilizing a sinusoidal interpolation method according to an embodiment of the present invention is a white light interferometer (white_light_interferometry) that obtains the shape of a sample by analyzing interference fringes generated by reflected measurement light and reflected light after white light is irradiated onto the sample and the mirror, respectively. The white light interferometer includes a CCD image sensor (Charge_Coupled_Device_image_sensor) that generates a plurality of interference fringe images by photographing the interference fringes, and an image analysis processor that generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) by accumulating the plurality of interference fringe images. The image analysis processor generates an interpolated white light interference fringe signal (I[n]′) by interpolating the generated white light interference fringe signal (I[n]) through a sinusoidal interpolation method (Sinusoidal_Interpolation), and calculates the surface information of the sample by analyzing the interpolated white light interference fringe signal (I[n]′).

[0020] The image analysis processor interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method. Based on the white light interference fringe signal (I[n]), it generates an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]), and then interpolates the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through the synusoid interpolation method to generate an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]'). Based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), it generates the interpolated white light interference fringe signal (I[n]').

[0021] When the image analysis processor generates the amplitude graph (A[n]) and the phase graph (θ[n]) based on the white light interference fringe signal (I[n]), it extracts the amplitude and phase components from the white light interference fringe signal (I[n]), respectively, to generate linear amplitude graphs (A[n]) and phase graphs (θ[n]).

[0022] The linear amplitude graph (A[n]) is the envelope of the white light interference fringe signal (I[n]) that is tangent to all of the peak points of the white light interference fringe signal (I[n]).

[0023] When the image analysis processor interpolates the amplitude graph (A[n]) and the phase graph (θ[n]) using the synusoid interpolation method, it calculates an interpolated value (A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively. The interpolated value (A[n+0.5], θ[n+0.5]) is the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]).

[0024] When the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), it generates the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]').

[0025] The measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively, and the measured values ​​(A[n]', θ[n]') of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), respectively, are all the same.

[0026] When the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), it determines the intensity value of the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) or interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'). When the measured value (A[n]) of the interpolated amplitude graph (A[n]') is at its maximum, when the phase of the interpolated phase graph (θ[n]') is 0°, and when the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph is greater than -90° but less than 90°, the intensity value of the interpolated white light interference fringe signal (I[n]') has a positive (+) value corresponding to the measured value (A[n]) or interpolated value (A[n+0.5]) of the interpolated amplitude graph (A[n]'). When the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph exceeds 90° to 270°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a negative (-) value corresponding to the measured value (A[n]) or interpolated value (A[n+0.5]) of the interpolated amplitude graph (A[n]′). When the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph is -90°, 90°, and 270°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a value of 0.

[0027] To achieve the above-mentioned objectives, a synusoidal interpolation method for a white light interferometer according to one embodiment of the present invention is a synusoidal interpolation method for a white light interferometer in which an image analysis processor generates an interpolated white light interference fringe signal (I[n]′) by interpolating the white light interference fringe signal (I[n]) through a synusoidal interpolation method. The synusoid interpolation method for the white light interferometer comprises the steps of: the image analysis processor generating an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]) based on the white light interference fringe signal (I[n]); the image analysis processor generating an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through the synusoid interpolation method; and the image analysis processor generating the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]').

[0028] The process by which the image analysis processor generates an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]) based on the white light interference fringe signal (I[n]) includes the process by which the image analysis processor generates a linear amplitude graph (A[n]) and a phase graph (θ[n]) by extracting the amplitude and phase components, respectively, from the white light interference fringe signal (I[n]).

[0029] The process by which the image analysis processor generates a linear amplitude graph (A[n]) and a phase graph (θ[n]) by extracting the amplitude and phase components of the white light interference fringe signal (I[n]), respectively, comprises the process by which the image analysis processor generates the amplitude graph (Envelope) by extracting the amplitude component (A[n]) of the white light interference fringe signal (I[n]) based on the following <Equation 1>, and generates the phase graph (Phase) by extracting the phase component (θ[n]) of the white light interference fringe signal (I[n]).

[0030] A[n](Envelope)=(c[n] 2 +s[n] 2 ) 1 / 2 . θ[n](Phase)=Atan(s[n],c[n]). <Formula 1> (Here, A[n] is the amplitude of the pixel in the white light interference fringe signal (Amplitude_on_Pixel_of_WLI_Fringe). θ[n] is the phase of the pixel in the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe). c[n] is the cosine component of the white light interference fringe signal (Cosine_Component_of_WLI_Fringe), calculated as c[n]=A[n]×cos(θ[n]). s[n] is the sine component of the white light interference fringe signal (Sine_Component_of_WLI_Fringe), calculated as s[n]=A[n]×sin(θ[n]).

[0031] The step by which the image analysis processor generates an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through the synusoid interpolation method includes a step by which the image analysis processor calculates an interpolated value (A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]). The interpolated value (A[n+0.5], θ[n+0.5]) is the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]).

[0032] The process by which the image analysis processor calculates interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured values ​​(A[n], θ[n]) and the second measured values ​​(A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]) respectively, includes the process by which the image analysis processor calculates interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured values ​​(A[n], θ[n]) and the second measured values ​​(A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]) respectively, based on the following <Equation 2>.

[0033] A[n+0.5]=0.5*(A[n]+A[n+1]). θ[n+0.5]=0.5*(θ[n]+θ[n+1]). <Formula 2> (Here, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude_on_Pixel_of_WLI_Fringe), and θ[n] is the phase of the white light interference fringe signal at the pixel (Phase_on_Pixel_of_WLI_Fringe)).

[0034] The step by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]') comprises the step by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]').

[0035] The process by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]') comprises the process by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]') based on the following <Equation 3>.

[0036] I[n] = A[n] × cos(θ[n]). <Formula 3> (Here, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude_on_Pixel_of_WLI_Fringe), and θ[n] is the phase of the white light interference fringe signal at the pixel (Phase_on_Pixel_of_WLI_Fringe)). [Effects of the Invention]

[0037] According to the present invention, a white light interferometer utilizing the synusoid interpolation method and the synusoid interpolation method for the white light interferometer, it is possible to naturally represent the shape of interference fringes by interpolating the interference fringes acquired from a CCD image sensor through the synusoid interpolation method.

[0038] According to the present invention, a white light interferometer utilizing the synusoid interpolation method and the synusoid interpolation method for the white light interferometer make it possible to quickly and accurately interpolate interference fringes acquired from a CCD image sensor by utilizing the mathematical conditions of the synusoid wavelength.

[0039] According to the present invention, which provides a white light interferometer utilizing the synusoid interpolation method and a synusoid interpolation method for the white light interferometer, the synusoid interpolation method has advantages that make it advantageous for acceleration on GPUs and the like through numerical optimization. [Brief explanation of the drawing]

[0040] [Figure 1] This figure shows a simplified example of a white light interferometer utilizing the synusoid interpolation method according to the present invention. [Figure 2] This figure shows the process by which the white light interference fringe signal generated by the image analysis processor according to the present invention is interpolated. [Figure 3] This figure shows the white light interference fringe signals of the same sample due to a change in phase, and the process by which those white light interference fringe signals are interpolated. [Figure 4] This figure shows how the image analysis processor according to the present invention generates an interpolated white light interference fringe signal by interpolating the white light interference fringe signal through the synusoid interpolation method. [Figure 5] This figure provides a simplified explanation of the synusoid interpolation method of the image analysis processor according to the present invention. [Figure 6] This is a flowchart of the synusoid interpolation method for a white light interferometer according to the present invention. [Figure 7] This is a flowchart of the synusoid interpolation method for a white light interferometer according to the present invention. [Figure 8]This is a flowchart of the synusoid interpolation method for a white light interferometer according to the present invention. [Modes for carrying out the invention]

[0041] Some embodiments of the present invention will be described in detail below with reference to illustrative drawings. It should be noted that when assigning reference numerals to the components in each figure, the same component will, to the greatest extent possible, have the same reference numeral when shown in other drawings.

[0042] Furthermore, in describing embodiments of the present invention, if it is determined that a specific description of a related known configuration or function would hinder the understanding of the embodiments of the present invention, such detailed description will be omitted.

[0043] Furthermore, when describing the components of the embodiments of the present invention, it is possible to use terms such as first, second, A, B, (a), (b), etc. Such terms are used solely to distinguish a component from other components, and do not limit the essence, order, or sequence of the component in question.

[0044] In this specification, the singular form also includes the plural form unless otherwise specified. The terms “includes” and / or “encompasses” as used in this specification do not preclude the presence or addition of one or more other components besides those mentioned.

[0045] The present invention will be described in more detail below with reference to the attached drawings. Figure 1 is a simplified diagram showing one embodiment of a white light interferometer 100 utilizing the synusoid interpolation method according to the present invention.

[0046] The white light interferometer 100 (hereinafter referred to as "white light interferometer 100") utilizing the synusoid interpolation method according to the present invention, as shown in Figure 1, comprises a light source 10, a beam splitter 20, a mirror 30, a stage 40, a stage movement assembly 50, a CCD image sensor 60, and an image analysis processor 70.

[0047] The light source 10 generates white light. The light source 10 supplies the white light to the beam splitter 20. The beam splitter 20 splits the white light supplied from the light source 10 and supplies it to the sample 41 and the mirror 30.

[0048] A sample 41 is placed on the upper surface of the stage 40. The sample 41 is the object to be measured for which surface information is to be measured. The sample 41 may be a nanostructure such as a semiconductor device. The stage movement assembly 50 moves the stage 40 either towards or away from the beam splitter 20. That is, the stage movement assembly 50 moves the stage 40 in the path axis direction (Z axis direction) of the white light supplied from the beam splitter 20 to the stage 40. The stage movement assembly 50 can move the stage 40 in the path axis direction (Z axis direction) of the white light based on a fine z_step_size (e.g., λ / 8, which is 68.75 nm). The movement of the stage 40 by the stage movement assembly 50 generates a fine path difference between the measurement light and the reflected light transmitted to the CCD image sensor 60.

[0049] Mirror 30 has a reflective surface on one side that faces the beam splitter 20. The beam splitter 20 divides the path of white light provided by the light source 10 into two paths: one for the sample 41 and the other for the mirror 30. The beam splitter 20 provides a portion of the white light from the light source 10 to the stage 40 and the remaining white light to the mirror 30.

[0050] The beam splitter 20 modulates the path of white light so that a portion of the white light provided from the light source 10 is transmitted to the stage 40 and the sample 41. The white light transmitted to the sample 41 is reflected back to the beam splitter 20 as measurement light and is transmitted through the beam splitter 20 to the CCD image sensor 60.

[0051] The beam splitter 20 provides the mirror 30 with the remaining white light from the light source 10. The white light that has been provided to the mirror 30 is reflected and transmitted back to the beam splitter 20. The beam splitter 20 changes the path of the reflected light so that the reflected light reflected by the mirror 30 is transmitted to the CCD image sensor 60.

[0052] The beam splitter 20 splits the white light into two streams: one for the sample 41 and the other for the reflective surface of the mirror 30. The measurement light reflected by the sample 41 and the reflected light reflected by the mirror 30 are transmitted to the CCD image sensor 60 by the beam splitter 20. Interference fringes are generated between the measurement light reflected by the sample 41 and the reflected light reflected by the mirror 30 due to subtle changes in the path difference.

[0053] With the beam splitter 20 at the center, the light source 10 side, the sample 41 side, the mirror 30 side, and the CCD image sensor 60 side may each include additional lenses (not shown) for focusing white light, measurement light, and reflected light, respectively.

[0054] The CCD image sensor 60 (Charge_Coupled_Device_image_sensor) receives the measurement light reflected from the sample 41 and the reflected light reflected from the mirror 30 from the beam splitter 20. The CCD image sensor 60 captures interference fringes of pixels generated by the measurement light and reflected light at predetermined time intervals while the stage 40 is moving in the Z-axis direction in steps by a constant z_step_size by the stage moving assembly 50. The CCD image sensor 60 generates multiple interference fringe images by capturing interference fringes at predetermined time intervals. Here, a pixel means a unit pixel contained in the XY plane of the interference fringe image. The CCD image sensor 60 transmits the multiple interference fringe images captured at predetermined time intervals to the image analysis processor 70.

[0055] The image analysis processor 70 generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) as shown in Figure 2(a) by accumulating multiple interference fringe images received from the CCD image sensor 60.

[0056] Figure 2 shows the interpolation process of the white light interference fringe signal generated by the image analysis processor 70 according to the present invention. Specifically, Figure 2(a) shows a graph of the white light interference fringe signal generated by the image analysis processor 70. Figure 2(b) shows an enlarged view of the main part of the graph of the white light interference fringe signal shown in Figure 2(a). Figure 2(c) shows an enlarged view of the main part of the graph of the interpolated white light interference fringe signal.

[0057] Figure 3 shows the white light interference fringe signal of the same sample 41 due to a phase change, and the process by which the white light interference fringe signal is interpolated. The white light interferometer 100 according to the present invention is equipped with all known white light interferometers that can acquire the shape of a sample 41 by analyzing interference fringes generated by the measurement light and reflected light, which are produced after white light is split by a beam splitter 20 and irradiated onto a sample 41 and a mirror 30, respectively. In this case, the white light interferometer 100 is equipped with a CCD image sensor 60 that generates multiple interference fringe images by capturing interference fringes, as is known, and an image analysis processor 70 that generates a white light interference fringe signal by accumulating the components contained in the multiple interference fringe images and calculates surface information of the sample 41 by analyzing the generated white light interference fringe signal.

[0058] The white light interference fringe signal is a graph that represents the cumulative effect of the intensity of each pixel, where the x-axis coordinate is the intensity of each of the multiple interference fringe pixels captured at predetermined time intervals as the stage 40 moves in steps along the Z-axis according to a constant z_step_size, and the y-axis coordinate is the position of the sample 41 which is changed by the movement of the stage 40.

[0059] The white light interference fringe signal generated by the image analysis processor 70 is shown in Figure 2(a). The central part of the white light interference fringe signal contains a key region (a) where the intensity of the interference fringes changes abruptly. A magnified view of this key region (a) is shown in Figure 2(b).

[0060] As shown in Figure 2(b), the white light interference fringe signal has a problem in that the shape of the white light interference fringe signal is unnaturally represented because the z_step_size of the stage movement assembly 50, which moves the stage 40 in the z-axis direction at predetermined time intervals when the interference fringe is captured, i.e., the movable length of the stage 40 in the z-axis direction is physically limited (e.g., λ / 8, or 68.75 nm). Thus, the limited movable distance of the stage 40 due to physical limitations imposes limitations on the representation, analysis, and interpretation of the white light interference fringe.

[0061] For example, referring to Figure 3, the raw white light interference fringe signals generated by photographing sample 41 appear to have different shapes depending on the position of stage 40, i.e., the phase change of the measured light, even when using the same sample 41. This occurs because the current white light interferometer 100 cannot accurately represent minute height changes within the z_step_size (e.g., 68.75 nm) of stage 40. However, by interpolating the raw white light interference fringe signals several times (2, 4, and 8 times, etc.), the shapes of each interpolated white light interference fringe signal gradually become identical.

[0062] Traditionally, as mentioned above, the unnatural shape of white light interference fringes (WLI_Fringe) due to such restrictive Z_Step_Size has been resolved by interpolating using spline interpolation (Cubic_Spline). However, spline interpolation is computationally intensive, which limits the speed of generating and analyzing white light interference fringes.

[0063] Furthermore, polynomial interpolation also has limitations in its application to white light interference fringe signals that have sinusoidal wavelengths. For example, polynomial interpolation requires coefficients of different orders. The number of data points required for fitting is Fitting_Order+1, but when sampling Sin and Cos_Waves at 90° intervals, accuracy is only achieved by using a 3rd or 4th order polynomial approximation. However, the problem is that applying a 3rd or 4th order polynomial approximation is difficult because there are 3 points within each interval.

[0064] In contrast, the sinusoidal interpolation method according to the present invention requires a minimum of two points for interpolation. By interpolating the midpoints between Slowly Varying Profile Points, accurate Sin and Cos Fitting is achieved. The sinusoidal interpolation method according to the present invention has the advantage of being able to apply interpolation while reliably adhering to the Sin and Cos Wave conditions.

[0065] The image analysis processor 70 according to the present invention generates an interpolated white light interference fringe signal (I[n]′) by interpolating the white light interference fringe signal (I[n]) shown in Figures 2(a) and (b) through sinusoidal interpolation. The image analysis processor 70 is capable of calculating surface information of the sample 41 by analyzing the interpolated white light interference fringe signal (I[n]′).

[0066] Figure 4 shows how the image analysis processor 70 according to the present invention generates an interpolated white light interference fringe signal by interpolating the white light interference fringe signal through synusoid interpolation. Specifically, Figure 4(a) shows the raw white light interference fringe signal graph generated by the image analysis processor 70. Figure 4(b) shows the amplitude graph and phase graph generated by the image analysis processor 70 by splitting the raw white light interference fringe signal into amplitude and phase components, respectively. Figure 4(c) shows the interpolated graph of the amplitude graph and phase graph generated by the image analysis processor 70, respectively. Figure 4(d) shows the interpolated white light interference fringe signal graph obtained by synthesizing the interpolated amplitude graph and phase graph through synusoid interpolation. Figures 4(a) to (d) show only the essential parts of the white light interference fringe signal in a simplified manner, as shown in Figure 2.

[0067] The image analysis processor 70 according to the present invention interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method. When the image analysis processor 70 interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method, it calculates the value between two measured values ​​in the white light interference fringe signal (I[n]) and generates an interpolated white light interference fringe signal (I[n]') by applying the calculated value. That is, the image analysis processor 70 calculates the median (mid-point) between two measured values ​​in the white light interference fringe signal (I[n]) and interpolates the white light interference fringe signal by applying the result.

[0068] The image analysis processor 70 according to the present invention calculates the median between two measured values ​​and interpolates the white light interference fringe signal (I[n]) to achieve higher resolution at exponential values ​​of 2 (e.g., x2, x4, and x8). In the case of x8 interpolation, the z_step_size is reduced from 68.75 nm to 8.6 nm.

[0069] In the following section, the interpolation of the white light interference fringe signal (I[n]) of the image analysis processor 70 will be described in detail with reference to Figure 4. The image analysis processor 70 according to the present invention interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method. As shown in Figure 4(a), the initially generated white light interference fringe signal (I[n]) is divided into amplitude and phase components, respectively, as shown in Figure 4(b), thereby generating an amplitude signal graph (Envelope, A[n]) and a phase signal graph (Phase, θ[n]). Then, as shown in Figure 4(c), the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) are interpolated by calculating the median value through the synusoid interpolation method and applying that calculated value, respectively, thereby generating an interpolated amplitude signal graph (A[n]′) and an interpolated phase signal graph (θ[n]′). As shown in Figure 4(d), interpolation of the white light interference fringe signal (I[n]) using the synusoid interpolation method is completed by generating an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0070] For fundamental white light interference fringe signals (I[n]), cosine (Cos) components, sine (Sin) components, etc., the amount of change per z_step of the interference fringe has a fast variation (Fast_Variation) similar to the maximum (Max) value. Therefore, for sinusoidal wavelengths such as fundamental white light interference fringe signals (I[n]), it is difficult to immediately calculate the correction value.

[0071] However, the amplitude signal graph (Envelope, A[n]) and phase signal graph (Phase, θ[n]) extracted from the basic white light interference fringe signal (I[n]) have a linear slow variation. Therefore, by applying linear interpolation to each of the linear amplitude signal graph (Envelope, A[n]) and linear phase signal graph (Phase, θ[n]), it is possible to easily interpolate each graph (A[n], θ[n]). Furthermore, by converting the interpolated results (A[n]', θ[n]') into a white light interference fringe signal with a synusoidal wavelength, it is possible to generate an interpolated white light interference fringe signal (I[n]').

[0072] As shown in Figure 4(b), the image analysis processor 70 according to the present invention generates an amplitude signal graph (A[n]) and a phase signal graph (θ[n]) by dividing the basic white light interference fringe signal (I[n]) into amplitude and phase components, respectively. When the image analysis processor 70 generates an amplitude signal graph (A[n]) and a phase signal graph (θ[n]) based on the white light interference fringe signal (I[n]), it generates linear amplitude graphs (A[n]) and phase graphs (θ[n]) by extracting the amplitude and phase components from the basic white light interference fringe signal (I[n]), respectively.

[0073] In this case, the linear amplitude signal graph (A[n]) may be an envelope that is tangent to all of the maximum amplitudes in each ascending and descending section of the white light interference fringe signal (I[n]). That is, in this case, the linear amplitude signal graph (A[n]) may be an envelope that is tangent to all of the peak points of the white light interference fringe signal (I[n]) within the envelope of the white light interference fringe signal (I[n]).

[0074] The image analysis processor 70 according to the present invention, as an example, when generating an amplitude signal graph (A[n]) and a phase signal graph (θ[n]) by dividing a basic white light interference fringe signal (I[n]) into components by amplitude (Amplitude) and phase (Phase), respectively, extracts a component (A[n]) by amplitude in the white light interference fringe signal (I[n]) based on the following <Equation 1> to generate an amplitude signal graph (Envelope). And it is possible to generate the phase signal graph (Phase) by extracting a component (θ[n]) by phase.

[0075] A[n](Envelope)=(c[n] 2 +s[n] 2 ) 1 / 2 . θ[n](Phase)=Atan(s[n],c[n]). <Equation 1> Here, A[n] is the amplitude (Amplitude_on_Pixel_of_WLI_Fringe) of the pixel of the basic white light interference fringe signal. θ[n] is the phase (Phase_on_Pixel_of_WLI_Fringe) of the pixel of the basic white light interference fringe signal. c[n] is the cosine component (Cosine_Component_of_WLI_Fringe) of the white light interference fringe signal, and is calculated by c[n]=A[n]×cos(θ[n]). s[n] is the sine component (Sine_Component_of_WLI_Fringe) of the white light interference fringe signal, and is calculated by s[n]=A[n]×sin(θ[n]).

[0076] <Equation 1> means the calculation of the Slowly_Varying component of WLI_Fringe (I[n]). Here, A[n](Envelope)=(c[n] 2 +s[n] 2 ) 1 / 2 uses the Sqrt function. θ[n](Phase)=Atan(s[n],c[n]) uses the Atan function.

[0077] As shown in Figure 4(c), the image analysis processor 70 according to the present invention calculates the median of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) through synusoid interpolation, and then interpolates them by applying the calculated value to generate an interpolated amplitude signal graph (A[n]′) and an interpolated phase signal graph (θ[n]′).

[0078] The image analysis processor 70 interpolates the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) using the synusoid interpolation method, respectively, and calculates an interpolated value (A[n+0.5], θ[n+0.5]) which is the median between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]). Here, the interpolated value (A[n+0.5], θ[n+0.5]) may be the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]).

[0079] The image analysis processor 70, when interpolating based on an amplitude signal graph (A[n]) using the synusoid interpolation method, centers the maximum value among the measured values ​​of the amplitude signal graph (A[n]) and calculates an interpolated value which is the median between that maximum value and the measurement value closest to that maximum value. For example, if the first measured value of the amplitude signal graph is A[1], the second measured value may be A[2], where the interpolated value may be A[1.5]. A[1.5] is calculated to have the average value of A[1] and A[2]. The image analysis processor 70 calculates A[n+0.5], which is the median of multiple measured values ​​A[n] and A[n+1], and applies this calculated value to the amplitude signal graph (A[n]) to generate an interpolated amplitude signal graph (A[n]') which has the interpolated value.

[0080] Similarly, when the image analysis processor 70 interpolates a phase signal graph (θ[n]) using synusoidal interpolation, it is possible to calculate an interpolated value which is the median between a certain measurement of the phase signal graph (θ[n]) and the measurement closest to it. For example, if the first measurement of the phase signal graph is θ[1], the second measurement may be θ[2], where the interpolated value may be θ[1.5]. θ[1.5] is calculated to have the average value of the values ​​of θ[1] and θ[2]. The image analysis processor 70 calculates θ[n+0.5], which is the median of multiple measurements θ[n] and θ[n+1], and applies this calculated value to the phase signal graph (θ[n]) to generate an interpolated phase signal graph (θ[n]′) which has the interpolated value.

[0081] As one embodiment, when the image analysis processor 70 generates an interpolated amplitude signal graph (A[n]′) and an interpolated phase signal graph (θ[n]′) by interpolating the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) respectively through synusoidal interpolation, it calculates the interpolated values ​​(A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) based on the following <Equation 2>.

[0082] A[n+0.5]=0.5*(A[n]+A[n+1]). θ[n+0.5]=0.5*(θ[n]+θ[n+1]). <Formula 2> Here, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude_on_Pixel_of_WLI_Fringe). θ[n] represents the phase of the white light interference fringe signal at the pixel (Phase_on_Pixel_of_WLI_Fringe).

[0083] Formula 2 is a formula for linear interpolation on binary upsampling of A[n] and θ[n], and is also a formula for calculating the correction value corresponding to Subindex(n+0.5).

[0084] The image analysis processor 70 according to the present invention completes the interpolation of the white light interference fringe signal (I[n]) using the synusoid interpolation method by generating an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0085] When the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]'), it generates the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0086] That is, the respective measured values ​​(A[n], θ[n]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), and the respective measured values ​​(A[n]', θ[n]') of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]') have the same value. For example, referring to both the amplitude signal graph (A[n]) and the interpolated amplitude signal graph (A[n]') in Figure 4(b) and Figure 4(c), points located at the same coordinates on each graph (A[n], A[n]') represent the same measured values ​​in the amplitude signal graph (A[n]) and the interpolated amplitude signal graph (A[n]'). In contrast, points that are not represented in the amplitude signal graph (A[n]) but are newly represented in the interpolated amplitude signal graph (A[n]') represent the interpolated values ​​newly calculated in the interpolated amplitude signal graph (A[n]').

[0087] Similarly, points located at the same coordinates in the phase signal graph (θ[n]) in Figure 4(b) and the interpolated phase signal graph (θ[n]′) in Figure 4(c) represent the same measured values. Points newly represented in the interpolated phase signal graph (θ[n]′) in Figure 4(c) represent the interpolated values ​​newly calculated in the interpolated phase signal graph (θ[n]′).

[0088] When the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]'), it determines the intensity value of the interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) and / or interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0089] For example, in one embodiment, when the measured value (A[n]) of the interpolated amplitude signal graph (A[n]') is at its maximum, the phase of the interpolated phase signal graph (θ[n]') is 0°. When the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is greater than -90° and less than 90°, the intensity value of the interpolated white light interference fringe signal (I[n]') corresponding to the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the phase signal graph has a positive (+) value that corresponds to the measured value (A[n]) or interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]'). If the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is greater than 90° and / or between 270°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a negative (-) value corresponding to the measured value (A[n]) and / or interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]′). If the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph is -90°, 90°, and 270°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a value of 0.

[0090] More specifically, the image analysis processor 70 determines that when the phase of the interpolated phase signal graph (θ[n]') is 0° when the measured value (A[n]) of the interpolated amplitude signal graph (A[n]') is at its maximum, and the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is 0°, the intensity value of the corresponding interpolated white light interference fringe signal (I[n]') has a positive (+) value corresponding to the measured value (A[n]) and / or interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]'). When the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is 90°, the intensity value of the interpolated white light interference fringe signal (I[n]') has a value of "0". When the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is 180°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a negative (-) value corresponding to the measured value (A[n]) and / or interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]′). When the measured value (θ[n]) and / or interpolated value (θ[n+0.5]) of the interpolated phase signal graph is 45°, the intensity value of the interpolated white light interference fringe signal (I[n]′) has a positive (+) value corresponding to the measured value (A[n]) and / or interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]′). If the measured value (θ[n]) and / or the interpolated value (θ[n+0.5]) of the interpolated phase signal graph is 135°, then the intensity value of the interpolated white light interference fringe signal (I[n]′) has a negative (-) value corresponding to the measured value (A[n]) or the interpolated value (A[n+0.5]) of the interpolated amplitude signal graph (A[n]′).

[0091] As described above, the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0092] As one embodiment, when the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]'), it generates the interpolated white light interference fringe signal (I[n]') based on the measured values ​​(A[n], θ[n]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), respectively, and the interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]'), respectively, based on the following <Equation 3>.

[0093] I[n] = A[n] × cos(θ[n]). <Formula 3> Here, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude on Pixel of WLI Fringe). θ[n] represents the phase of the white light interference fringe signal at the pixel (Phase on Pixel of WLI Fringe). Equation 3 is the formula used to convert I[n+0.5] back from the calculated A[n+0.5] and θ[n+0.5].

[0094] Figure 5 is a diagram illustrating the synusoid interpolation method of the image analysis processor 70 according to the present invention. In the interpolation of the white light interference fringe signal (I[n]) using the sinusoidal interpolation method of the image analysis processor 70, as shown in Figure 5, Cos and Sin are calculated only at the mid-point (N-1 points), and a characteristic feature is that they are calculated using the sinusoidal method without using complex trigonometric functions. In the interpolation of the white light interference fringe signal (I[n]) using the sinusoidal interpolation method of the image analysis processor 70, the Amp (amplitude) at the mid-point is first generated (first order) by averaging the Amp values ​​of the two side points, and the remaining Amp values ​​are generated by moving average (Moving Averaging) of a total of 2N-1 Interpolated Pixels in 3 Pixel Step increments.

[0095] Figures 6 to 8 are flowcharts of the synusoid interpolation method of the white light interferometer 100 according to the present invention. The synusoidal interpolation method for the white light interferometer 100 according to the present invention generates an interpolated white light interference fringe signal (I[n]′) by interpolating the white light interference fringe signal (I[n]) through the synusoidal interpolation method in the image analysis processor 70.

[0096] The synusoid interpolation method for the white light interferometer 100 according to the present invention, as shown in Figures 6 to 8, comprises the steps of: (S100) an image analysis processor 70 generating an amplitude signal graph (Envelope, A[n]) and a phase signal graph (Phase, θ[n]) based on a white light interference fringe signal (I[n]); (S200) an interpolated amplitude signal graph (A[n]') and an interpolated phase signal graph (θ[n]') by interpolating the amplitude signal graph (A[n]) and the phase signal graph (θ[n]) respectively through the synusoid interpolation method; and (S300) an interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]').

[0097] Step (S100) includes a step (S110) in which the image analysis processor 70 extracts the amplitude and phase components from the white light interference fringe signal (I[n]), respectively, to generate a linear amplitude signal graph (A[n]) and a phase signal graph (θ[n]).

[0098] Step (S110) includes a step (S111) in which the image analysis processor 70 generates an amplitude signal graph (Envelope) by extracting the amplitude component (A[n]) from the white light interference fringe signal (I[n]) based on the following <Equation 1>, and generates a phase signal graph (Phase) by extracting the phase component (θ[n]) from the white light interference fringe signal (I[n]).

[0099] A[n](Envelope)=(c[n] 2 +s[n] 2 ) 1 / 2 . θ[n](Phase)=Atan(s[n],c[n]). <Formula 1> In <Equation 1>, A[n] is the amplitude on the pixel of the white light interference fringe signal. θ[n] is the phase on the pixel of the white light interference fringe signal. c[n] is the cosine component of the white light interference fringe signal, calculated as c[n]=A[n]×cos(θ[n]). s[n] is the sine component of the white light interference fringe signal, calculated as s[n]=A[n]×sin(θ[n]).

[0100] Step (S200) includes a step (S210) in which the image analysis processor 70 calculates an interpolation value (A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), respectively. The interpolation value (A[n+0.5], θ[n+0.5]) is calculated using the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]).

[0101] Step (S210) includes step (S211) in which the image analysis processor 70 calculates interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured values ​​(A[n], θ[n]) and the second measured values ​​(A[n+1], θ[n+1]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), respectively, based on the following <Equation 2>.

[0102] A[n+0.5]=0.5*(A[n]+A[n+1]). θ[n+0.5]=0.5*(θ[n]+θ[n+1]). <Formula 2> In <Equation 2>, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude_on_Pixel_of_WLI_Fringe). θ[n] is the phase of the white light interference fringe signal at the pixel (Phase_on_Pixel_of_WLI_Fringe).

[0103] Step (S300) includes a step (S310) in which the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0104] Step (S310) includes step (S311) in which the image analysis processor 70 generates an interpolated white light interference fringe signal (I[n]') based on the following <Equation 3>, using the measured values ​​(A[n], θ[n]) of the amplitude signal graph (A[n]) and the phase signal graph (θ[n]), and the interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude signal graph (A[n]') and the interpolated phase signal graph (θ[n]').

[0105] I[n] = A[n] × cos(θ[n]). <Formula 3> In <Equation 3>, A[n] is the amplitude of the white light interference fringe signal at the pixel (Amplitude_on_Pixel_of_WLI_Fringe). θ[n] is the phase of the white light interference fringe signal at the pixel (Phase_on_Pixel_of_WLI_Fringe).

[0106] The terms used in this specification are defined as shown in Table 1 below.

[0107] [Table 1]

[0108] In detail, I[n] represents the basic white light interference fringe signal measured by the white light interferometer 100 according to the present invention. Each value (x-axis on the graph) represents the intensity (or strength) of the interference fringe and can be expressed as I[n]=A[n]cos(θ[n])+IDC-Offset. A[n] represents the amplitude of the white light interference fringe signal at the pixels (Amplitude_on_Pixel_of_WLI_Fringe), and A[n]=(c[n] 2 +s[n] 2 ) 1 / 2 It can be expressed as follows: θ[n] represents the phase on the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe), and can be expressed as θ[n]=Atan(s[n],c[n]). c[n] is the cosine component of the white light interference fringe signal (Cosine_Component_of_WLI_Fringe), and can be expressed as c[n]=A[n]×cos(θ[n]). s[n] is the sine component of the white light interference fringe signal (Sine_Component_of_WLI_Fringe), and can be expressed as s[n]=A[n]×sin(θ[n]).

[0109] In this specification, the image analysis processor 70 may comprise a processor that executes a series of execution processes stored in memory. Alternatively, the image analysis processor 70 may operate as a software module driven and controlled by a processor. Furthermore, the image analysis processor 70 may be a hardware device.

[0110] For reference, the synusoid interpolation method of the white light interferometer 100 according to one embodiment of the present invention is embodied in a program instruction form that can be executed through various computer means and can be written to a computer-readable medium. The computer-readable medium may contain program instructions, data files, data structures, etc., individually or in combination. The program instructions written to the medium may be specifically designed and configured for the present invention or may be publicly known and usable by those skilled in the art of computer software. Examples of computer-readable media may include magnetic media such as hard disks, floppy disks (registered trademarks), and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROMs, RAMs, and flash memory. Examples of program instructions include not only machine code, such as that produced by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the present invention, and vice versa.

[0111] The scope of protection of the present invention is not limited to the descriptions and expressions of the embodiments explicitly described above. Furthermore, it should be added once again that the scope of protection of the present invention is not limited by obvious modifications or substitutions in the art to which the present invention pertains.

Claims

1. A white light interferometer that utilizes synusoid interpolation, the white light interferometer is A light source that provides white light, The stage on which the sample is placed, A stage movement assembly for moving the stage in the axis direction of the white light path, A mirror having a reflective surface, A beam splitter that divides the path of the white light provided by the light source into the sample side and the mirror side, A CCD image sensor (Charge_Coupled_Device_image_sensor) receives measurement light reflected from the sample and reflected light reflected from the mirror from the beam splitter while the stage is moving in the path axis direction by the stage moving assembly, and generates multiple interference fringe images by capturing the interference fringes generated by the measurement light and the reflected light, and An image analysis processor that generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) by accumulating multiple interference fringe images, It is equipped with, The image analysis processor is characterized by generating an interpolated white light interference fringe signal (I[n]') by interpolating the generated white light interference fringe signal (I[n]) through sinusoidal interpolation. A white light interferometer utilizing synusoid interpolation.

2. When the image analysis processor interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method, The white light interference fringe signal (I[n]) is divided into amplitude and phase components, respectively, to generate an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]), The amplitude graph (A[n]) and the phase graph (θ[n]) are interpolated using the synusoid interpolation method to generate an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]'), respectively. The interpolated white light interference fringe signal (I[n]') is generated based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), characterized in that A white light interferometer utilizing the synusoid interpolation method described in claim 1.

3. When the image analysis processor generates the amplitude graph and the phase graph by dividing the white light interference fringe signal into amplitude and phase components, The method is characterized by generating an amplitude graph (Envelope) by extracting the amplitude component (A[n]) from the white light interference fringe signal (I[n]) based on the following <Equation 1>, and generating a phase graph (Phase) by extracting the phase component (θ[n]) from the white light interference fringe signal (I[n]), A[n](Envelope)=(c[n] ２ +s[n] ２ ) １／２ 、 θ[n] (Phase) = Atan(s[n], c[n]), <Equation 1> Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe), c[n] is the cosine component of the white light interference fringe signal, calculated as c[n] = A[n] × cos(θ[n]), s[n] is the sine component of the white light interference fringe signal, calculated as s[n] = A[n] × sin(θ[n]). A white light interferometer utilizing the synusoid interpolation method described in claim 2.

4. When the image analysis processor generates an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through a synusoid interpolation method, The method is characterized by calculating interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively, based on the following <Equation 2>. A[n+0.5]=0.5*(A[n]+A[n+1]), θ[n+0.5]=0.5*(θ[n]+θ[n+1]), <Equation 2> is, Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe). A white light interferometer utilizing the synusoid interpolation method described in claim 3.

5. When the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), Based on the following <Equation 3>, the interpolated white light interference fringe signal (I[n]') is generated based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'). I[n]=A[n]×cos(θ[n]), <Equation 3> Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe). A white light interferometer utilizing the synusoid interpolation method described in claim 4.

6. A white light interferometer utilizing the synusoid interpolation method, wherein the shape of the sample is obtained by analyzing the reflected measurement light and the interference fringes generated by the reflected light after white light has been irradiated onto the sample and a mirror, respectively, the white light interferometer utilizes the synusoid interpolation method, A CCD image sensor (Charge_Coupled_Device_image_sensor) that generates multiple interference fringe images by capturing the aforementioned interference fringes, and An image analysis processor that generates a white light interference fringe signal (WLI_Fringe_signal, I[n]) by accumulating multiple interference fringe images, It is equipped with, The image analysis processor is characterized by generating an interpolated white light interference fringe signal (I[n]') by interpolating the generated white light interference fringe signal (I[n]) through sinusoidal interpolation. A white light interferometer utilizing synusoid interpolation.

7. When the image analysis processor interpolates the white light interference fringe signal (I[n]) using the synusoid interpolation method, Based on the white light interference fringe signal (I[n]), an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]) are generated, The amplitude graph (A[n]) and the phase graph (θ[n]) are interpolated using the synusoid interpolation method, respectively, to generate an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]'). The interpolated white light interference fringe signal (I[n]') is generated based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), characterized in that A white light interferometer utilizing the synusoid interpolation method described in claim 6.

8. When the image analysis processor generates the amplitude graph (A[n]) and the phase graph (θ[n]) based on the white light interference fringe signal (I[n]), The method is characterized by generating linear amplitude graphs (A[n]) and phase graphs (θ[n]) by extracting the amplitude and phase components, respectively, from the white light interference fringe signal (I[n]). A white light interferometer utilizing the synusoid interpolation method described in claim 7.

9. The linear amplitude graph (A[n]) is, The envelope of the white light interference fringe signal (I[n]) is characterized by being tangent to all of the peak points of the white light interference fringe signal (I[n]). A white light interferometer utilizing the synusoid interpolation method described in claim 8.

10. When the image analysis processor interpolates the amplitude graph (A[n]) and the phase graph (θ[n]) using the synusoid interpolation method, The interpolation values ​​(A[n+0.5], θ[n+0.5]) are calculated between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively. The interpolated value (A[n+0.5], θ[n+0.5]) is characterized by being the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]). A white light interferometer utilizing the synusoid interpolation method described in claim 8.

11. When the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), The interpolated white light interference fringe signal (I[n]') is generated based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'). A white light interferometer utilizing the synusoid interpolation method described in claim 10.

12. The measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively, The measured values ​​(A[n]', θ[n]') of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), They are characterized by having the same value as each other. A white light interferometer utilizing the synusoid interpolation method described in claim 11.

13. When the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), Based on the measured values ​​(A[n], θ[n]) or interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), the intensity value (intensity_value) of the interpolated white light interference fringe signal (I[n]') is determined. When the measured value (A[n]) of the interpolated amplitude graph (A[n]') is at its maximum, and the phase of the interpolated phase graph (θ[n]') is 0°, If the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph is greater than -90° but less than 90°, the intensity value of the interpolated white light interference fringe signal (I[n]') has a positive (+) value corresponding to the measured value (A[n]) or interpolated value (A[n+0.5]) of the interpolated amplitude graph (A[n]'), When the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph exceeds 90° to 270°, the intensity value of the interpolated white light interference fringe signal (I[n]') has a negative (-) value corresponding to the measured value (A[n]) or interpolated value (A[n+0.5]) of the interpolated amplitude graph (A[n]'). When the measured value (θ[n]) or interpolated value (θ[n+0.5]) of the interpolated phase graph is -90°, 90°, and 270°, the intensity value of the interpolated white light interference fringe signal (I[n]') is characterized by having a value of "0". A white light interferometer utilizing the synusoid interpolation method described in claim 12.

14. A synusoidal interpolation method for a white light interferometer, wherein an image analysis processor generates an interpolated white light interference fringe signal (I[n]') by interpolating a white light interference fringe signal (I[n]) through a synusoidal interpolation method, The synusoid interpolation method for white light interferometry is The image analysis processor performs the steps of generating an amplitude graph (Envelope, A[n]) and a phase graph (Phase, θ[n]) based on the white light interference fringe signal (I[n]), The image analysis processor generates an interpolated amplitude graph (A[n]') and an interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through a synusoid interpolation method, and The image analysis processor performs the steps of generating the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), Features include, Synusoid interpolation method for white light interferometry.

15. The process by which the image analysis processor generates the amplitude graph (Envelope, A[n]) and the phase graph (Phase, θ[n]) based on the white light interference fringe signal (I[n]) is as follows: The image analysis processor is characterized by comprising a step of generating linear amplitude graphs (A[n]) and phase graphs (θ[n]) by extracting the amplitude and phase components of the white light interference fringe signal (I[n]), respectively. The synusoid interpolation method for a white light interferometer according to claim 14.

16. The process by which the image analysis processor extracts the amplitude and phase components from the white light interference fringe signal (I[n]) respectively to generate a linear amplitude graph (A[n]) and a phase graph (θ[n]) is as follows: The image analysis processor is characterized by comprising the steps of generating an amplitude graph (Envelope) by extracting the amplitude component (A[n]) in the white light interference fringe signal (I[n]) based on the following <Equation 1>, and generating a phase graph (Phase) by extracting the phase component (θ[n]) in the white light interference fringe signal (I[n]), A[n](Envelope)=(c[n] ２ +s[n] ２ ) １／２ 、 θ[n] (Phase) = Atan(s[n], c[n]), <Equation 1> Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe), c[n] is the cosine component of the white light interference fringe signal, calculated as c[n] = A[n] × cos(θ[n]), s[n] is the sine component of the white light interference fringe signal, calculated as s[n] = A[n] × sin(θ[n]). The synusoid interpolation method for a white light interferometer according to claim 15.

17. The process by which the image analysis processor generates the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]') by interpolating the amplitude graph (A[n]) and the phase graph (θ[n]) respectively through synusoidal interpolation is as follows: The image analysis processor includes a step of calculating interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured values ​​(A[n], θ[n]) and the second measured values ​​(A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively. The interpolated value (A[n+0.5], θ[n+0.5]) is characterized by being the average value of the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]). The synusoid interpolation method for a white light interferometer according to claim 14.

18. The process by which the image analysis processor calculates interpolation values ​​(A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]) respectively, is as follows: The image analysis processor is characterized by comprising a step of calculating the interpolation value (A[n+0.5], θ[n+0.5]) between the first measured value (A[n], θ[n]) and the second measured value (A[n+1], θ[n+1]) of the amplitude graph (A[n]) and the phase graph (θ[n]) respectively, based on the following <Equation 2>, A[n+0.5]=0.5*(A[n]+A[n+1]), θ[n+0.5]=0.5*(θ[n]+θ[n+1]), <Equation 2> is, Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe). The synusoid interpolation method for a white light interferometer according to claim 17.

19. The process by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]') is as follows: The image analysis processor is characterized by comprising a step of generating an interpolated white light interference fringe signal (I[n]') based on the respective measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), and the respective interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'). The synusoid interpolation method for a white light interferometer according to claim 14.

20. The process by which the image analysis processor generates the interpolated white light interference fringe signal (I[n]') based on the measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively, and the interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), respectively, is as follows: The image analysis processor is characterized by comprising the step of generating the interpolated white light interference fringe signal (I[n]') based on the measured values ​​(A[n], θ[n]) of the amplitude graph (A[n]) and the phase graph (θ[n]), respectively, and the interpolated values ​​(A[n+0.5], θ[n+0.5]) of the interpolated amplitude graph (A[n]') and the interpolated phase graph (θ[n]'), respectively, based on the following <Equation 3>, I[n]=A[n]×cos(θ[n]), <Equation 3> Here, A[n] is the amplitude of the pixel of the white light interference fringe signal (Amplitude on Pixel of WLI Fringe), θ[n] is the phase of the pixel of the white light interference fringe signal (Phase_on_Pixel_of_WLI_Fringe). The synusoid interpolation method for a white light interferometer according to claim 19.

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