Real-time automatic focusing method based on interference fringe phase extraction

Abstract

The invention discloses a real-time automatic focusing method based on interference fringe phase extraction, and the method specifically comprises the steps: importing an initial interference image, setting a focusing state position as an initial phase shift value, and carrying out the zero setting of the initial phase shift value; when the detection system runs, keeping interference image video stream input, and calculating a phase shift value and a phase value in real time through an improved iterative algorithm; and the calculation result is converted into a defocusing value, and the PZT controller is controlled to complete focusing. According to the automatic focusing method provided by the invention, the defocusing amount is obtained according to the phase movement of the interference fringes, a high-precision displacement measurement method is introduced into the automatic focusing technology, and compared with a traditional microscopic focusing method, the focusing precision is improved in a breakthrough manner, and the method has very high innovativeness; based on an interference image method, phase information closest to reality is extracted through iterative operation, real-time processing is continuously carried out through video streams of interference images, the operation speed is high, and real-time focusing can be completed in the scanning process of a detection system.

Description

Technical Field

[0001] The invention belongs to the technical field of optical detection, and in particular relates to a real-time automatic focusing method based on interference fringe phase extraction. Background Art

[0002] Acquiring wafer surface morphology features through microscopic imaging technology is an important method for wafer defect detection, but the depth of field of the microscopic optical system is small, and image blur is easy to occur during the scanning process. The wafer defect detection system requires automatic control of the xyz three axes. The surface of the wafer as a whole is an uneven curved surface. The movement of the stage on the xy plane will cause a slight change in the object distance, which will cause the imaging system to defocus. Therefore, real-time focusing must be performed to ensure the accuracy of the microscope focus.

[0003] The main purpose of autofocus technology in defect detection systems is to solve the defocus problem during the scanning process. The existing commonly used laser focusing method directly determines the focus state by the shape of the light spot. This method is difficult to break through the diffraction limit and cannot guarantee the detection rate in the face of nano-level wafer precision.

[0004] In view of the above shortcomings, the real-time autofocusing method based on interference fringe phase extraction proposed in the present invention can achieve a breakthrough in accuracy and can accurately complete real-time autofocusing with a quarter-wavelength accuracy. Summary of the invention

[0005] In order to make up for the shortcomings of the prior art, the present invention aims to provide a real-time autofocus method based on interference fringe phase extraction, realize measurement by interference technology, collect interference fringe images, and use the physical quantity relationship between phase shift and object distance change to complete the defocus measurement, so as to solve the accuracy that the original autofocus method cannot meet.

[0006] The technical problem solved by the present invention can be achieved through the following technical solutions: The real-time auto-focusing method based on interference fringe phase extraction specifically comprises the following steps: Step 1, import the initial interference image, set the focus state position to the initial phase shift value and set it to zero; Step 2: When the detection system is running, the interference image video stream input is maintained, and the phase shift value and phase value are calculated in real time through the improved iterative algorithm; that is, the initial phase information is substituted into the iterative algorithm to obtain the phase shift amount, and then the phase shift amount is used as the initial phase shift amount to be brought into the iterative algorithm to solve the phase value, and multiple iterations are performed until convergence to obtain the accurate value; then the accurate value is compared with the focus evaluation value calculated by the current grayscale to determine the degree of error accumulation. If a large error occurs, the difference is compensated proportionally to output the physical quantity; Step 3: Convert the calculation result into a defocus value and control the PZT (lead zirconate titanate material) controller to complete focusing.

[0007] Furthermore, when the detection system is running, steps 2 and 3 are executed simultaneously in multiple threads, and feedback is provided to each other to complete the closed loop.

[0008] Furthermore, the improved iterative algorithm is based on the aia (Advanced Iterative Algotithm) algorithm and the grayscale gradient image clarity algorithm. The aia algorithm is based on least squares fitting. It first fits and calibrates the actual phase shift value and then uses the least squares phase shift algorithm to solve the phase to be measured. The actual phase shift value does not need to be estimated at the beginning of the calculation. Through dozens of least squares fitting iterations, it can converge to obtain high-precision phase information; the iterative operation is performed around the residual function, and the sum of the squares of the light intensity differences of the pixels in each frame of the interference pattern is calculated, which is expressed as: , Where Sm is the residual function set, which is the sum of squares of the intensity difference between the measured and theoretical calculations; N is the total number of pixels; m represents the number of frames of the interference pattern, and n represents the number of pixels of the interference pattern. Represents the corresponding theoretical light intensity value, Represents the actual light intensity value collected; the phase shift obtained based on this needs to be judged for convergence, and the convergence criterion is: , In the formula, represents the phase shift value of the kth iteration of the mth frame image, represents the phase shift value of the k-1th iteration of the first frame image. This iteration setting ensures that the phase shift value converges to the global optimum; The grayscale gradient is calculated using the Laplace operator to roughly calculate the focus evaluation value. When the value is the largest, it is in the focus state, expressed as: , In the formula, E represents the focus evaluation value, I represents the light intensity value at that point, Indicates the location of the selected measurement point.

[0009] Furthermore, in step 2, it is determined whether the phase shift value meets the set convergence condition. When the condition is met, the current phase shift value and phase value information are obtained; otherwise, the phase shift amount and phase value are recalculated iteratively; the current phase shift value and phase value changes are compared with the focus evaluation value changes. If a sudden change occurs, it means that the error is large enough to have a certain impact on the measurement accuracy, and the change difference is substituted into the phase shift value and phase value information for compensation.

[0010] Furthermore, in step 3, in the area where two or more light spots overlap, the coherence condition of the light wave is satisfied, that is, the frequency is the same, the vibration direction is the same, and the phase difference is constant. The basic expression for the light intensity of the interference image of the phase shift signal is: , in, is the total light intensity; It is the DC component of the interference light intensity, generally called background light intensity; To modulate the light intensity; represents the position of the pixel point of the interference pattern, is the phase value in the reference beam, is the phase shift value in the reference beam; Introducing Gaussian white noise, which is the most common noise in practice, into the model of phase-shifting interferogram , and a new interference image expression is obtained: , In the formula, In order to introduce noise, the optical path of the measuring arm and the optical path of the reference arm determine the wavefront phase of the two beams of light. The relationship between the phase difference and the optical path difference is expressed as: , In the formula, is the optical path of the measuring arm, is the optical path of the reference arm, is the wavelength of the light source.

[0011] Furthermore, light intensity data can be acquired through camera collection. There are four unknown quantities in the light intensity expression, namely background light intensity, modulated light intensity, phase to be measured and phase shift value. These unknown quantities can be obtained by collecting three interference patterns with different phase shift values.

[0012] Furthermore, the detection system includes a deep ultraviolet laser light source, an interference optical system, a CMOS (Complementary Metal Oxide Semiconductor) camera, a host computer and a control system. The deep ultraviolet laser light source is used to provide light energy to the autofocus system and the defect detection system at the same time; the interference optical system is used to split the monochromatic light and produce interference phenomenon; the CMOS camera is used to collect interference fringe images; the host computer is used to extract phase information through image processing technology to give the defocus amount; the control system is used to control the z-axis drive; the detection system determines the change of object distance through the movement of the interference fringe phase, and controls the z-axis movement to maintain the focus state.

[0013] Compared with the prior art, the present invention has the following advantages: (1) The autofocus method proposed in the present invention obtains the defocus amount according to the phase shift of the interference fringes, and introduces a high-precision displacement measurement method into the autofocus technology. Compared with the traditional microscopic focusing method, it has a breakthrough in improving the focusing accuracy and is highly innovative. Considering that the relative displacement measurement method has certain inapplicability in microscopic focusing, this method cannot be directly applied to the autofocus system. Therefore, the original algorithm is improved in combination with the image clarity evaluation algorithm, which can greatly reduce the impact of errors.

[0014] (2) The present invention is based on the interference image method, which extracts the phase information that is closest to reality through iterative calculations, and continuously processes the interference image video stream in real time. The calculation speed is fast, and real-time focusing can be completed during the scanning process of the detection system. Due to the optical characteristics of interference itself, the defocus amount that exceeds the diffraction limit accuracy can be extracted through the phase information in the interference fringes, realizing nanometer-level automatic focusing. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the method of the present invention; Figure 2 This is a structural diagram of the wafer defect detection system of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] like Figure 1 As shown, the real-time auto-focusing method based on interference fringe phase extraction includes the following specific steps: Step 1: Import the initial interference image, set the focus state position to the initial phase shift value and set it to zero.

[0018] Step 2: When the detection system is running, the interference image video stream is input, and the phase shift value and phase value are calculated in real time through the improved iterative algorithm.

[0019] The initial phase information is substituted into the iterative algorithm to obtain the phase shift, and then the phase shift is used as the initial phase shift to the iterative algorithm to solve the phase value. Multiple iterations are performed until convergence to obtain the precise value. The precise value is then compared with the focus evaluation value calculated from the current grayscale to determine the degree of error accumulation. If a large error occurs, the difference is compensated proportionally to output the physical quantity.

[0020] The improved iterative algorithm is based on the aia algorithm and the grayscale gradient image clarity algorithm. The aia algorithm is based on least squares fitting. First, the actual phase shift value is fitted and calibrated, and then the least squares phase shift algorithm is used to solve the phase to be measured. The actual phase shift value does not need to be estimated at the beginning of the calculation. Through dozens of least squares fitting iterations, the convergence can be completed to obtain high-precision phase information; the iterative operation is performed around the residual function, and the square sum of the light intensity difference of the pixel points of each frame of the interference pattern is calculated, which is expressed as: , Where Sm is the residual function set, which is the sum of squares of the intensity difference between the measured and theoretical calculations; N is the total number of pixels; m represents the number of frames of the interference pattern, and n represents the number of pixels of the interference pattern. Represents the corresponding theoretical light intensity value, Represents the actual light intensity value collected; the phase shift obtained based on this needs to be judged for convergence, and the convergence criterion is: , In the formula, represents the phase shift value of the kth iteration of the mth frame image, Represents the phase shift value of the k-1th iteration of the first frame image. This iteration setting ensures that the phase shift value converges to the global optimum.

[0021] Determine whether the phase shift value meets the set convergence conditions. If the conditions are met, obtain the current phase shift value and phase value information; otherwise, recalculate the phase shift and phase value iteratively. Compare the current phase shift and phase value changes with the focus evaluation value changes. If a sudden change occurs, it means that the error is large enough to have a certain impact on the measurement accuracy. Substitute the change difference into the phase shift and phase value information for compensation.

[0022] The focus evaluation value is obtained by the focus evaluation calculation method based on the Laplace operator, and compared with the proposed output physical quantity information to determine whether the error is too large. If it is too large, the difference is proportionally compensated to the proposed output value. The focus evaluation value is expressed as: , In the formula, E represents the focus evaluation value, I represents the light intensity value at that point, Indicates the location of the selected measurement point.

[0023] Step 3: convert the calculated result into a defocus value and control the PZT controller to complete focusing.

[0024] Among them, piezoelectric ceramic PZT is the abbreviation of lead zirconate titanate material. The industry often refers to high-precision motion controllers made of this material as PZT. The phase difference φ=2π / λ×δ, δ is the optical path difference, and the defocus amount is calculated by phase conversion. An electrical signal is sent to the PZT controller to drive it to move an equal distance in the opposite direction of the defocus direction to complete the focusing.

[0025] In the area where two or more light spots overlap, the coherence conditions of the light waves are met, that is, the same frequency, the same vibration direction, and a constant phase difference. The basic expression for solving the light intensity of the interference image of the phase shift signal (the light intensity data can be collected by the camera, and there are four unknown quantities in the light intensity expression: background light intensity, modulated light intensity, phase to be measured, and phase shift value, which can be obtained by collecting three interference patterns with different phase shift values) is: , in, is the total light intensity; It is the DC component of the interference light intensity, generally called background light intensity; To modulate the light intensity; represents the position of the pixel point of the interference pattern, is the phase value in the reference beam, is the phase shift value in the reference beam; Introducing Gaussian white noise, which is the most common noise in practice, into the model of phase-shifting interferogram , and a new interference image expression is obtained: , In the formula, In order to introduce noise, the optical path of the measuring arm and the optical path of the reference arm determine the wavefront phase of the two beams of light. The relationship between the phase difference and the optical path difference is expressed as: , In the formula, is the optical path of the measuring arm, is the optical path of the reference arm, is the wavelength of the light source.

[0026] The detection system of the present application includes a deep ultraviolet laser light source, an interference optical system, a CMOS (Complementary Metal Oxide Semiconductor, which is a material that can be used as an image sensor chip. Cameras are usually divided into CCD cameras and CMOS cameras according to the type of image sensor) camera, a host computer and a control system. The deep ultraviolet laser light source is used to provide light energy to the autofocus system and the defect detection system at the same time; the interference optical system is used to split monochromatic light and produce interference phenomenon; the CMOS camera is used to collect interference fringe images; the host computer is used to extract phase information through image processing technology to give the defocus amount; the control system is used to control the z-axis drive; the detection system determines the change of object distance by the movement of the interference fringe phase, and controls the z-axis movement to maintain the focus state.

[0027] Step 2 of this application will accumulate errors during the operation of the system, and step 3 can compensate for the errors. When the detection system is running, steps 2 and 3 are multi-threaded and run simultaneously, and feedback from each other completes a closed loop. The lens depth of field of the detection system is within 200nm, and the surface of the wafer appears as a partially concave and convex surface. The change in object distance during the scanning process deviates from the depth of field, which will cause the captured image to be blurred. In order to integrate the optical path system, the entire device requires the autofocus system and the wafer defect detection system to share the same light source. The light passes through the reference arm and measurement arm of the optical system to reach the camera in the form of interference fringes. The optical path difference between the reference light and the measurement light, that is, the defocus amount, is calculated through phase calculation, and then the PZT controller is driven to complete the focusing.

[0028] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A real-time autofocus method based on interference fringe phase extraction, characterized in that: The specific steps include: Step 1, import the initial interference image, set the focus state position to the initial phase shift value and set it to zero; Step 2: When the detection system is running, the interference image video stream input is maintained, and the phase shift value and phase value are calculated in real time through the improved iterative algorithm; that is, the initial phase information is substituted into the iterative algorithm to obtain the phase shift amount, and then the phase shift amount is used as the initial phase shift amount to be brought into the iterative algorithm to solve the phase value, and multiple iterations are performed until convergence to obtain the accurate value; then the accurate value is compared with the focus evaluation value calculated by the current grayscale to determine the degree of error accumulation. If a large error occurs, the difference is compensated proportionally to output the physical quantity; Step 3: Convert the calculation result into a defocus value and control the PZT controller to complete focusing.

2. The real-time auto-focusing method based on interference fringe phase extraction according to claim 1, characterized in that: When the detection system is running, steps 2 and 3 are multi-threaded and run simultaneously, with mutual feedback to complete the closed loop.

3. The real-time auto-focusing method based on interference fringe phase extraction according to claim 1, characterized in that: The improved iterative algorithm is based on the aia algorithm and the grayscale gradient image clarity algorithm. The aia algorithm is based on least squares fitting. First, the actual phase shift value is fitted and calibrated, and then the least squares phase shift algorithm is used to solve the phase to be measured. The actual phase shift value does not need to be estimated at the beginning of the calculation. Through dozens of least squares fitting iterations, the convergence can be completed to obtain high-precision phase information; the iterative operation is performed around the residual function, and the square sum of the light intensity difference of the pixel points of each frame of the interference pattern is calculated, which is expressed as: ， Where Sm is the residual function, which is the sum of squares of the measured and theoretically calculated light intensity differences; N is the total number of pixels; m represents the number of frames of the interference pattern, and n represents the number of pixels of the interference pattern. Represents the corresponding theoretical light intensity value, Represents the actual light intensity value collected; the phase shift obtained based on this needs to be judged for convergence, and the convergence criterion is: ， In the formula, represents the phase shift value of the kth iteration of the mth frame image, Represents the phase shift value of the k-1th iteration of the first frame image; The grayscale gradient is calculated using the Laplace operator to calculate the focus evaluation value. When the value is the largest, it is in the focus state, which is expressed as: ， In the formula, E represents the focus evaluation value, I represents the light intensity value at that point, Indicates the location of the selected measurement point.

4. The real-time auto-focusing method based on interference fringe phase extraction according to claim 3, characterized in that: In step 2, it is determined whether the phase shift value meets the set convergence condition. When the condition is met, the current phase shift value and phase value information are obtained; Otherwise, the phase shift and phase value are recalculated iteratively; the current phase shift and phase value changes are compared with the focus evaluation value changes. If a sudden change occurs, it means that the error is large enough to have a certain impact on the measurement accuracy. The change difference is substituted into the phase shift and phase value information for compensation.

5. The real-time auto-focusing method based on interference fringe phase extraction according to claim 1, characterized in that: In step 3, in the area where two or more light spots overlap, the coherence conditions of the light waves are met, that is, the frequency is the same, the vibration direction is the same, and the phase difference is constant. The basic expression for the light intensity of the interference image of the phase shift signal is: ， in, is the total light intensity; is the DC component of the interference light intensity, is the background light intensity; To modulate the light intensity; represents the position of the pixel point of the interference pattern, is the phase value in the reference beam, is the phase shift value in the reference beam; Introducing Gaussian white noise into the model of phase-shifting interferogram , and a new interference image expression is obtained: ， In the formula, In order to introduce noise, the optical path of the measuring arm and the optical path of the reference arm determine the wavefront phase of the two beams of light. The relationship between the phase difference and the optical path difference is expressed as: ， In the formula, is the optical path of the measuring arm, is the optical path of the reference arm, is the wavelength of the light source.

6. The real-time auto-focusing method based on interference fringe phase extraction according to claim 5, characterized in that: Light intensity data can be collected by a camera. There are four unknown quantities in the light intensity expression: background light intensity, modulated light intensity, phase to be measured, and phase shift value. The data can be obtained by collecting three interference patterns with different phase shift values.

7. The real-time auto-focusing method based on interference fringe phase extraction according to any one of claims 1 to 6, characterized in that: The detection system includes a deep ultraviolet laser light source, an interference optical system, a CMOS camera, a host computer and a control system. The deep ultraviolet laser light source is used to provide light energy to the autofocus system and the defect detection system at the same time; the interference optical system is used to split the monochromatic light and produce interference phenomenon; the CMOS camera is used to collect interference fringe images; the host computer is used to extract phase information through image processing technology to give the defocus amount; the control system is used to control the z-axis drive; the detection system determines the change of object distance through the movement of the interference fringe phase, and controls the z-axis movement to maintain the focus state.

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