Optical detection method and system, device and storage medium

Abstract

An optical inspection method, system, device, and storage medium are disclosed for detecting the height difference between a feature portion and a reference portion on the surface of an object under test. The method includes: acquiring an inspection image of the object under test; acquiring a first region of interest (ROI) and a second region of interest (ROI) of the inspection image, wherein the first ROI includes image information of the feature portion and the second ROI includes image information of the reference portion; obtaining first inspection information of the feature portion based on the first ROI, and obtaining second inspection information of the reference portion based on the second ROI; and obtaining the height difference between the feature portion and the reference portion based on the first and second inspection information. This invention is advantageous for obtaining more accurate inspection information, while saving computing power, improving inspection efficiency, and achieving highly stable and high-precision optical inspection.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of optical detection, and in particular to an optical detection method, system, device and storage medium. Background Technology

[0002] With the rapid development of integrated circuit manufacturing technology, advanced packaging forms such as 2.5D / 3D integration and wafer-level packaging have become the main direction of packaging technology development.

[0003] With the high-density development of integrated circuit manufacturing, package sizes are getting smaller and smaller, and interconnection density is increasing. In integrated circuits, the size and spacing of the bumps connecting chips are getting smaller and smaller. At the same time, the problem of interconnection short circuits caused by solder deformation is becoming increasingly prominent. Therefore, the demand for three-dimensional defect detection of chip bump coplanarity is becoming more urgent.

[0004] Currently, optical inspection methods are commonly used for three-dimensional defect detection. Summary of the Invention

[0005] The problem solved by the embodiments of the present invention is to provide an optical detection method, system, device and storage medium to achieve high stability and high precision optical detection.

[0006] To address the aforementioned problems, embodiments of the present invention provide an optical detection method for detecting the height difference between a feature portion and a reference portion on the surface of an object to be tested. The detection method includes: acquiring a detection image of the object to be tested; acquiring a first region of interest and a second region of interest in the detection image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; obtaining first detection information of the feature portion based on the first region of interest and obtaining second detection information of the reference portion based on the second region of interest; and obtaining the height difference between the feature portion and the reference portion based on the first and second detection information.

[0007] This invention also provides an optical detection system for detecting the height difference between a feature portion and a reference portion on the surface of an object to be tested. The detection system includes: a detection image acquisition module for acquiring a detection image of the object to be tested; a region of interest acquisition module for acquiring a first region of interest and a second region of interest of the detection image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; a detection information acquisition module for obtaining first detection information of the feature portion based on the first region of interest and second detection information of the reference portion based on the second region of interest; and a height difference acquisition module for obtaining the height difference between the feature portion and the reference portion based on the first and second detection information.

[0008] Compared with the prior art, the technical solution of the embodiments of the present invention has the following advantages:

[0009] In the optical detection method provided by this invention, a first region of interest (ROI) and a second region of interest (ROI) of the detection image are acquired. The first ROI includes image information of the feature portion, and the second ROI includes image information of the reference portion. First detection information of the feature portion is obtained based on the first ROI, and second detection information of the reference portion is obtained based on the second ROI. The measured height difference between the feature portion and the reference portion is obtained based on the first and second detection information. By acquiring the first and second ROIs of the detection image, this invention obtains the first detection information of the feature portion and the second detection information of the reference portion, which is beneficial for obtaining more accurate detection information, while saving computing power, improving detection efficiency, and achieving high-stability and high-precision optical detection. Attached Figure Description

[0010] Figure 1 A flowchart of an embodiment of the detection method of the present invention;

[0011] Figure 2 and Figure 3 This is a schematic diagram of the detection device and optical path corresponding to an embodiment of the detection method of the present invention;

[0012] Figure 4 yes Figure 3 A magnified view of any one of the convex points to be tested;

[0013] Figure 5 This is a top view of the detection device corresponding to one embodiment of the detection method of the present invention;

[0014] Figure 6 This is a schematic diagram of an embodiment of one-dimensional projection;

[0015] Figure 7 This is a schematic diagram of an embodiment for obtaining a first region of interest and a second region of interest;

[0016] Figure 8 This is a functional block diagram of an embodiment of the detection system of the present invention;

[0017] Figure 9 This is a hardware structure diagram of an embodiment of the device provided by the present invention. Detailed Implementation

[0018] As the background technology shows, optical inspection is a commonly used technique for detecting features on an object. However, the accuracy of existing optical inspection methods needs improvement, requiring better parameter setting methods to achieve high stability and high precision in optical inspection.

[0019] To address the aforementioned technical problem, embodiments of the present invention provide an optical detection method for detecting the height difference between a feature portion and a reference portion on the surface of an object to be tested. The detection method includes: acquiring a detection image of the object to be tested; acquiring a first region of interest and a second region of interest in the detection image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; obtaining first detection information of the feature portion based on the first region of interest and obtaining second detection information of the reference portion based on the second region of interest; and obtaining the height difference between the feature portion and the reference portion based on the first and second detection information.

[0020] The embodiments of the present invention obtain first detection information of the feature part and second detection information of the reference part by acquiring the first region of interest and the second region of interest of the detection image, which is beneficial to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0021] To make the above-mentioned objects, features and advantages of the embodiments of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] refer to Figure 1 , Figure 1 This is a flowchart of an embodiment of the detection method of the present invention.

[0023] In this embodiment, the detection method includes the following steps:

[0024] Step S1: Acquire the detection image of the object to be tested, which includes the image information of the object to be tested;

[0025] Step S2: Obtain the first region of interest and the second region of interest of the detected image. The first region of interest includes image information of the feature region, and the second region of interest includes image information of the reference region.

[0026] Step S3: Obtain first detection information of the feature part based on the first region of interest, and obtain second detection information of the reference part based on the second region of interest;

[0027] Step S4: Obtain the measured height difference between the feature portion and the reference portion based on the first detection information and the second detection information.

[0028] The embodiments of the present invention obtain first detection information of the feature part and second detection information of the reference part by acquiring the first region of interest and the second region of interest of the detection image, which is beneficial to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0029] The following section explains each step of the detection method in conjunction with the detection system.

[0030] Reference Figures 2 to 7 , Figure 2 and Figure 3 This is a schematic diagram of the detection device and optical path corresponding to an embodiment of the detection method of the present invention. Figure 4 yes Figure 3 A magnified view of a local part of any convex point to be tested. Figure 5 This is a top view of the detection device corresponding to one embodiment of the detection method of the present invention. Figure 6 This is a schematic diagram of one-dimensional projection embodiment. Figure 7 This is a schematic diagram of an embodiment for obtaining a first region of interest and a second region of interest. The detection method described in this embodiment will be explained in detail.

[0031] In this embodiment, optical detection is used to detect the height of the feature portion, and the reference portion on the surface of the object to be measured is used as the detection reference for detecting the height of the feature portion. That is, the measured height difference between the feature portion and the reference portion on the surface of the object to be measured is used as the height detection of the feature portion.

[0032] Specifically, refer to Figure 2 and Figure 3 The feature part is the bump 101 to be measured, and the reference part is the wafer surface at the bottom of the bump 101 to be measured. The detection method of this embodiment is used to measure the microscopic three-dimensional morphology of the height of the bump 101 to be measured.

[0033] Step S1: Obtain the detection image of the test object 100.

[0034] The detection image is acquired to prepare for subsequent acquisition of image information of the feature area and the reference area.

[0035] In this embodiment, optical detection is adapted to form an incident light spot 800s on the surface of the test object 100 with sampling points by incident light (e.g., Figure 5 As shown), the detector 810 collects signal light from the sampling point to obtain the measurement height of the feature based on the signal light. The sampling point includes the feature and the reference part.

[0036] Specifically, in this embodiment, acquiring the detection image of the object to be tested 100 includes: forming an incident light spot 800s on the surface of the object to be tested 100 by incident light, and forming signal light by reflection from the surface of the object to be tested 100; and acquiring the detection image corresponding to the incident light spot 800s by the detector 810 collecting the signal light.

[0037] In this embodiment, the optical detection method is suitable for scanning the object 100 to obtain multiple detection images of the object 100.

[0038] In this embodiment, optical detection is suitable for scanning the test object 100 using an incident light spot 800s.

[0039] Specifically, in this embodiment, incident light is reflected on the surface of the object to be tested 100 to form signal light, which forms a triangular optical path, thereby using triangulation to detect the height of the feature.

[0040] In other embodiments, a dispersive spectrometer or a confocal microscope may be used to detect the height.

[0041] As an example, the test object 100 with sampling points is a wafer, and the optical inspection in this embodiment is used to detect three-dimensional defects related to the coplanarity of bumps on the wafer surface. In other embodiments, the test object can also be a mobile phone case, a chip, a glass surface, etc.

[0042] In this embodiment, the sampling point also includes the reference portion of the surface of the object to be tested 100.

[0043] This embodiment obtains the measured height difference between the feature and the reference part by performing optical detection on the sampling point, thereby obtaining the actual measured height of the feature.

[0044] In this embodiment, a detection image of the object to be tested 100 is acquired by a detector 810. The detector 810 includes a first detector 820 and a second detector 830 for alternating detection scans (e.g., ...). Figure 3 (As shown).

[0045] In this embodiment, two detectors 810 work alternately to collect imaging information of incident light spot 810s and incident light spot 820s respectively until the object under test is linearly scanned, which helps to improve detection efficiency.

[0046] In other embodiments, the detector may also include only one detector (e.g. Figure 2 (As shown).

[0047] In this embodiment, the incident angle α of the incident light is less than 45 degrees or greater than 45 degrees.

[0048] In this embodiment, the incident angle of the incident light is less than 45 degrees, which is beneficial to reduce the probability of the feature portion on the test object 100 being blocked by flexibly adjusting the incident angle of the incident light, so that the feature portion can be fully illuminated, thereby making the imaging of the feature portion more accurate. The incident angle of the incident light is greater than 45 degrees, which is beneficial to increase the space above the test object 100 by flexibly adjusting the incident angle of the incident light, so as to facilitate the installation of other detection devices.

[0049] In this embodiment, the incident angle of the incident light is 25 degrees to 35 degrees.

[0050] The incident light undergoes specular reflection on the surface of the object under test 100. The incident angle of the incident light is equal to the reflection angle of the signal light. The incident angle of the incident light is 25 degrees to 35 degrees. This ensures that the feature area can receive more sufficient illumination, facilitates the setting of the relative positions of the illumination module and the imaging module in the detection equipment, and also facilitates the complete reception of the signal light by the imaging module, thereby facilitating the acquisition of more accurate imaging in the imaging module.

[0051] In this embodiment, the incident light spot 800s is strip-shaped, thus enabling the detection device to perform a linear scan of the object 100. In other embodiments, the incident light spot may also be a point spot or a region spot.

[0052] The object under test 100 is scanned using a strip-shaped incident light spot 800s. Along the scanning direction, the edges of adjacent linear incident light spots 800s can be aligned or partially overlapped. Using linear incident light spots 800s to complete linear scanning is beneficial for achieving complete coverage of all linear incident light spots 800s on the object under test 100. At the same time, it can make full use of each linear incident light spot 800s. A smaller number of linear incident light spots 800s are needed to complete the scanning of the object under test 100, thereby improving scanning efficiency.

[0053] Specifically, in conjunction with reference Figure 2 and Figure 3 The detection device for the detection method includes an illumination module, which includes components along the optical path transmission direction (e.g., Figure 2 and Figure 3 (As indicated by the arrow on the dashed line) A light source assembly 200, a first slit element 400, and a first mirror group 500 are arranged sequentially. The light source assembly 200 is used to generate a linear light beam, the first slit element 400 is used to allow the light beam to pass through and generate linear incident light, and the first mirror group 500 is used to focus the linear incident light onto the object under test 100 to generate a strip-shaped incident light spot 800s.

[0054] In this embodiment, along the optical path transmission direction, the light beam generated by the light source component 200 passes through the first slit element 400, thereby generating an incident light spot 800s on the object under test 100. Therefore, compared to a circular light beam, the light source component 200 generates a linear light beam. When the light beam generated by the light source component 200 is coupled with the first slit element 400, it is beneficial to reduce the waste of light beam energy and improve the coupling efficiency.

[0055] In this embodiment, the light source assembly 200 includes a light source and a shaping element 220. The light source is an incoherent light source, and the shaping element 220 is used to shape the light emitted by the light source to produce a linear beam.

[0056] In this embodiment, the light source is an incoherent light source. Compared with coherent light sources (e.g., laser light sources), incoherent light sources have less noise. Therefore, the light beam generated by the incoherent light source has a higher signal-to-noise ratio in the imaging module, thereby enabling the imaging module to obtain more accurate imaging information of the feature parts.

[0057] Specifically, in this embodiment, the type of light source includes LED light source, halogen lamp or xenon lamp.

[0058] In practical applications, incoherent light sources typically emit circular beams. Therefore, shaping element 220 is used to shape the light emitted by the light source to ensure that the light source assembly 200 produces a linear beam.

[0059] In this embodiment, the shaping element 220 includes an optical fiber bundle, the shape of the entrance port of the optical fiber bundle matching the shape of the light spot emitted by the light source, and the optical fibers at the exit port of the optical fiber bundle arranged in a straight line.

[0060] Using fiber optic bundles to shape the light emitted from a light source is simple and easy to operate. Furthermore, the port shape of the fiber optic bundle is easily adjustable, allowing the input port of the fiber optic bundle to be adjusted according to the light spot formation emitted by the light source, and the output port of the fiber optic bundle to be adjusted according to the required shape of the incident light.

[0061] In this embodiment, the shape of the incident port of the fiber bundle matches the shape of the light spot emitted by the light source, thereby improving the coupling efficiency between the light emitted by the light source and the fiber bundle. The shape of the exit port of the fiber bundle is straight, thereby enabling the light source assembly 200 to generate a linear beam.

[0062] In this embodiment, the light source assembly 200 further includes a filter color wheel for controlling the spectrum emitted by the light source assembly 200.

[0063] As an example, the light source assembly 200 includes a light box 210, in which a light source and a filter color wheel are disposed, the filter color wheel being used to control the spectrum emitted by the light box 210.

[0064] The light box 210 is used as a device for housing a light source and a color wheel of filters.

[0065] As an example, the light source emits white light, which, after passing through a color wheel with a filter, can cause the light box 210 to emit blue, green, yellow, or cyan light.

[0066] In this embodiment, the spectrum of the filter color wheel is adjusted according to the spectrum of the surface coating of the feature portion, for example, according to the spectrum of the coating on the wafer surface. Specifically, the spectrum of the filter color wheel is consistent with the spectrum of the surface coating of the feature portion, which helps to improve the signal-to-noise ratio of the signal light generated by the incident light on the surface of the feature portion.

[0067] In this embodiment, the length direction of the slit opening in the first slit element 400 is perpendicular to the incident surface of the incident light path, thereby obtaining linear incident light that matches the slit opening. Accordingly, in this embodiment, the length of the obtained linear incident light is controlled by setting the slit opening length of the first slit element 400.

[0068] The first lens group 500 is used to focus linear incident light onto the object under test to generate a linear light spot, and also to control the size of the generated linear light spot. As an example, the first lens group 500 is a first microscope objective.

[0069] In this embodiment, the size and spacing of the bumps to be tested are usually small. Therefore, a finer incident light spot of 800s is required to detect the bumps to be tested.

[0070] In this embodiment, the first lens group 500 is used to reduce the image of the first slit element 400 onto the object under test 100, thereby reducing the width of the linear incident light passing through the first slit element 400 and thus obtaining a narrower incident light spot 800s. When using the incident light spot 800s to perform linear scanning on the object under test 100, it is beneficial to improve the scanning accuracy and thus improve the accuracy of the detection results.

[0071] In this embodiment, the first slit element 400 and the first mirror group 500 are used to shape and image the light beam generated by the light source assembly 200. The first mirror group 500 can be used to reduce the size of the first slit element 400 and image it onto the test object 100, thereby obtaining a smaller incident light spot 800s. The incident light spot 800s passes through the test object 100 to form a signal light, which is beneficial to obtaining higher precision imaging information and correspondingly obtaining highly stable and accurate detection results.

[0072] In this embodiment, the lighting module further includes an optical fiber coupler 300, which is disposed between the light source assembly 200 and the first slit element 400. The optical fiber coupler 300 is used to couple the light beam to the slit opening of the first slit element 400.

[0073] In this embodiment, the light source component 200 generates a linear light beam through an optical fiber bundle. Since the light beam generated by the optical fiber bundle is a discontinuous light spot, the optical fiber coupler 300 can converge the light beam and couple it at the slit opening of the first slit element 400. This is beneficial to improve the illumination efficiency of the incident light, control the incident light, reduce the divergence of the incident light, and improve the uniformity of the imaging in the imaging module.

[0074] In this embodiment, the fiber optic coupler 300 includes a cylindrical mirror 310, which is disposed on the side of the fiber optic coupler 300 near the light-emitting end face, or disposed on the side of the optical fiber coupler near the light-incident end face.

[0075] Cylindrical mirror 310 is used to improve the illumination efficiency of incident light and the uniformity of incident light.

[0076] Step S2: Obtain the first region of interest (ROI) and the second region of interest of the detection image. The first ROI includes image information of the feature region, and the second ROI includes image information of the reference region.

[0077] The first region of interest is the area for detecting the feature part, and the second region of interest is the area for detecting the reference part. By obtaining the first region of interest for the feature part and the second region of interest for the reference part, relatively accurate imaging areas of the feature part and the reference part can be obtained. Separating the detection calculations for the feature part and the reference part is beneficial to improving detection efficiency and accuracy.

[0078] In this embodiment, obtaining the first region of interest and the second region of interest of the detection image includes: obtaining the distribution of light parameter values ​​of the detection image, wherein the distribution of light parameter values ​​is the correspondence between the position of each pixel in the detection image and the light parameter values, and wherein the light parameter values ​​include gray values.

[0079] The distribution of optical parameter values ​​represents the correspondence between the position of each pixel in the detection image and the optical parameter value. By utilizing the distribution of optical parameter values, the imaging situation at each position in the detection image can be obtained, thereby obtaining the ROI region corresponding to the sampling point. The optical parameter values ​​can include grayscale values.

[0080] Accordingly, in this embodiment, the first region of interest and the second region of interest in the detection image are selected based on the distribution of light parameter values.

[0081] In this embodiment, the detector 810 collects signal light to obtain image information corresponding to the incident light spot 800s.

[0082] Image information can characterize the optical parameter values ​​corresponding to each position on the target surface 80. By collecting signal light through detector 810, image information corresponding to the incident light spot 800s can be obtained, thereby enabling the distribution of optical parameter values ​​corresponding to each position on the target surface 80 through image information.

[0083] In this embodiment, taking the light parameter value as the gray value as an example, the obtained image information is a gray value matrix of m columns * n rows corresponding to the position of each point on the object under test 100, which is the gray value matrix of m columns * n rows corresponding to each pixel in the ROI.

[0084] Specifically, in this embodiment, the detection device includes an imaging module, which includes an imaging component 600 and a detector 810. The imaging component 600 is used to focus the signal light into the detector 810.

[0085] In this embodiment, at least a portion of the signal light is collected by detector 810, and imaging information of the sampling point is obtained based on the collected signal light. The imaging information includes the position of the sampling spot of the sampling point.

[0086] In this embodiment, the target surface 80 is perpendicular to the incident direction of the corresponding received signal light, thus simplifying the setup of the target surface 80 and reducing modifications to the original detection system.

[0087] Specifically, the detection device also includes a beam splitter 700, which is used to transmit the received signal light along multiple different optical path directions and project the signal light transmitted along multiple different optical path directions into detectors 810 respectively, and each detector 810 sequentially collects each signal light to form images of different areas of the object under test 100.

[0088] In this embodiment, the signal light transmitted by the beam splitter 700 along multiple different optical path directions is projected into the first detector 820 and the second detector 830 respectively.

[0089] In this embodiment, the imaging component 600 includes a second mirror group 620, an aperture 630, and a tube mirror 640 arranged sequentially along the optical path transmission direction. The second mirror group 620 is used to collect signal light and incident the signal light into the aperture 630. The tube mirror 640 is used to receive the signal light passing through the aperture 630 and converge the signal light.

[0090] In this embodiment, the second mirror group 620 is used to amplify the optical path of the signal light, making the imaging of the feature clearer. As an example, the second mirror group 620 is a second microscope objective.

[0091] In this embodiment, the aperture 630 is used to control the amount of light passing through the signal light. The aperture 630 is also used to limit the telecentricity of the main ray of the signal light, so that the telecentricity of the signal light is infinitely close to 0. This is beneficial to make the imaging quality of each field of view in the imaging module uniform, thereby helping to obtain imaging information with higher accuracy.

[0092] In this embodiment, the aperture 630 images the feature at infinity, and the tube lens 640 images the feature at a finite distance. Correspondingly, it images the feature onto the detector 810. The combination of the aperture 630 and the tube lens 640 helps to ensure that the signal light, after passing through the imaging component 600, has a uniform, clear, and accurate imaging quality on the detector 810.

[0093] In this embodiment, the imaging assembly 600 further includes a second slit element 610 disposed on the side of the second mirror group 620 facing away from the aperture stop 630. The second slit element 610 is used to reduce stray light of the signal light.

[0094] In this embodiment, the second slit element 610 is used to limit the numerical aperture (NA) of the optical system of the signal light, thereby reducing the divergence of the signal light.

[0095] In this embodiment, the distribution of optical parameter values ​​of sampling points is obtained based on the optical parameter values ​​of each point in the image information.

[0096] In this embodiment, the detector 810 collects signal light at different relative positions to obtain image information corresponding to each relative position.

[0097] The detector 810 collects signal light from sampling points at different relative positions to the object under test 100, thereby obtaining image information for each sampling point.

[0098] In this embodiment, obtaining the distribution of optical parameter values ​​of the detection image includes: performing one-dimensional projection of the image information of the detection image along a first direction to obtain first projection data. The first projection data represents the correspondence between the position of each pixel point and the projection value in a second direction. The projection value is the maximum value of the optical parameter value. The first direction is the row direction of the target surface 80 of the detector 810, and the second direction is the column direction of the target surface 80 of the detector 810.

[0099] Specifically, in this embodiment, the first direction is perpendicular to the detection scan direction, and the second direction is the detection scan direction (e.g., ...). Figure 5 (As shown in the X direction).

[0100] In this embodiment, the optical parameter value is taken as the grayscale value as an example, such as... Figure 6 As shown, any image information is projected in one dimension along the scanning direction perpendicular to the detection scan to obtain the first projection data, that is, the first projection column vector 1*n of the gray value matrix with m columns * n rows is obtained along the scanning direction perpendicular to the detection scan. The first projection column vector 1*n is the maximum value of the gray value in each row of the gray value matrix with m columns * n rows.

[0101] In this embodiment, obtaining the distribution of light parameter values ​​of the detection image further includes: stitching together the first projection data corresponding to multiple detection images along a first direction to obtain a data matrix.

[0102] By stitching together the first projection data corresponding to multiple detection images along the first direction, the overall image information of the object under test 100 after global scanning can be obtained, and the obtained data matrix is ​​the global grayscale value of the object under test 100.

[0103] As an example, in this embodiment, signal light is collected by the first detector 820 and the second detector 830. The total number of image information collected by each detector 810 is N, and each detector 810 obtains a data matrix of N columns * n rows.

[0104] In this embodiment, the data matrix is ​​projected in one dimension along the first direction to obtain second projection data. The second projection data represents the correspondence between the positions of multiple pixels in the second direction and the projection values. The projection values ​​are the maximum, minimum or average values ​​of the light parameter values.

[0105] A one-dimensional projection is performed on the data matrix along the first direction to obtain the second projection data, that is, the second projection column vector 1*n of the data matrix with N columns * n rows is obtained along the scanning direction perpendicular to the detection scan. The second projection column vector 1*n is the maximum, minimum or average value of the grayscale value of each row in the data matrix with N columns * n rows.

[0106] The second projection column vector 1*n represents the grayscale values ​​obtained after scanning all of the object under test 100 based on the grayscale value distribution of the image of the object under test 100. The grayscale values ​​in the second projection data can represent the grayscale value distribution at different positions along the scanning direction perpendicular to the detection scan. Thus, based on the grayscale value distribution, the positions of sampling points of different categories along the scanning direction perpendicular to the detection scan can be determined. Based on the global grayscale value distribution, the representation of the second projection data is more accurate.

[0107] In this embodiment, obtaining the first region of interest and the second region of interest based on the distribution of optical parameter values ​​includes: obtaining the peak position corresponding to the second projection data, including the first peak position corresponding to the first region and the second peak position corresponding to the second region; obtaining the first region of interest based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; obtaining the second region of interest based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position.

[0108] The peak position of the second projection data can characterize the point where the incident light is well reflected on the test object 100. The first peak position corresponds to the first region of interest, and the second peak position corresponds to the second region of interest. In this embodiment, the regions of the feature part and the reference part can be located by the peak position, so that the peak position corresponds one-to-one with the region of interest. The boundary of the region of interest is located on both sides of the peak position, so that the region of interest includes the signal light reflected by the incident light in the sampling point region.

[0109] Specifically, the region of the feature part is located by the first peak position, and the region of the reference part is located by the second peak position.

[0110] In this embodiment, obtaining a first region of interest based on a first peak position and obtaining a second region of interest based on a second peak position includes: obtaining a first location region of points that are continuous with the first peak position and whose projection values ​​are not zero based on the first peak position; obtaining a second location region of points that are continuous with the second peak position and whose projection values ​​are not zero based on the second peak position; obtaining a location range along a second direction that covers the first location region as the first region of interest based on the first location region; and obtaining a location range along the second direction that covers the second location region as the second region of interest based on the second location region.

[0111] like Figure 7 As shown, taking the second projection data as the average value as an example, the first position region of the point that is continuous with the first peak position and whose projection value is not 0 is obtained. This is the region of the signal light reflected by the incident light in the feature region. Thus, the first region of interest covers the first position region, which helps to ensure that all effective regions used to detect the feature are detected.

[0112] like Figure 7 As shown, taking the second projection data as an example, the second position region of the point that is continuous with the second peak position and whose projection value is not 0 is obtained. This is the region of the signal light reflected by the incident light in the reference region. Thus, the second region of interest covers the second position region, which helps to ensure that all effective regions used to detect the reference are detected.

[0113] In this embodiment, the first region of interest (e.g., the feature portion) is obtained. Figure 7 As shown in ROI1), and the second region of interest corresponding to the reference section (e.g. Figure 7 (as shown in ROI2).

[0114] In other embodiments, obtaining the first region of interest and the second region of interest based on the distribution of optical parameter values ​​may further include: determining a first region and a second region along a second direction based on the detected image, wherein the first region includes image information of a feature portion and the second region includes image information of a reference portion; obtaining the peak position corresponding to the first projection data, including a first peak position corresponding to the first region and a second peak position corresponding to the second region; obtaining the first region of interest based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; and obtaining the second region of interest based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position.

[0115] Execution step S3: Obtain first detection information of the feature part based on the first region of interest, and obtain second detection information of the reference part based on the second region of interest.

[0116] The first detection information is used to obtain the height of the feature portion, and the second detection information is used to obtain the height of the reference portion.

[0117] This embodiment obtains the first and second regions of interest in the detection image, and then obtains the first detection information of the feature part and the second detection information of the reference part, which is beneficial to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and achieving high stability and high precision optical detection.

[0118] In this embodiment, obtaining first detection information of the feature based on the first region of interest and second detection information of the reference part based on the second region of interest includes: obtaining the top centroid position of the feature based on the first region of interest and obtaining the bottom centroid position of the reference part based on the second region of interest.

[0119] The top and bottom centroid positions are used to calculate the relative height of the feature.

[0120] Specifically, in conjunction with reference Figure 4 In this embodiment, the incident angle α of the incident light is less than 45 degrees as an example. Figure 4 A magnified view of a portion of any of the convex points to be measured is shown for ease of explanation. Figure 4 The diagram illustrates the overlapping of two test bumps of different heights. The first test bump 101a is represented by a solid black bump, and the second test bump 101b is represented by a dashed outline. For the first test bump 101a, when incident light illuminates it, it is reflected at point P to form signal light (the optical path of the signal light reflected at point P is represented by a dashed line). The image spot on the target surface 80 is located at point P'. For the second test bump 101b, when incident light illuminates it, it is reflected at point Q to form signal light (the optical path of the signal light reflected at point P is represented by a solid line). The image spot on the target surface 80 is located at point Q'.

[0121] In this embodiment, the target surface 80 is perpendicular to the incident direction of the corresponding received signal light. Therefore, the conjugate image of the target surface 80 is located on the base surface 80e passing through point P. The base surface 80e is perpendicular to the main optical path 10b of the signal light. However, the incident angle α of the incident light is less than 45 degrees, and the incident light is specularly reflected. Therefore, the incident light and the signal light are not perpendicular. Thus, the base surface 80e and the optical axis 10a of the incident light do not coincide. That is to say, point Q on the second convex point 101b to be tested is not on the base surface 80e. As a result, the imaging spot of the incident light passing through point Q is a blur spot. In other words, point Q cannot be clearly imaged at point Q', but forms a blur spot at point Q'. Therefore, in order to obtain the clear position of point Q', it is necessary to process the blur spot.

[0122] In this embodiment, the center of the diffuse spot is extracted to obtain the center of the diffuse spot, which is the clear position of point Q', i.e., the centroid position.

[0123] In this embodiment, the methods for center extraction include gray-scale centroid method, quadratic curve fitting vertex method, Gaussian curve fitting vertex method, centroid method, or maximum value position method.

[0124] Gray-scale centroid method, quadratic curve fitting vertex method, Gaussian curve fitting vertex method, centroid method or maximum value position method are all commonly used methods for center extraction in the field of optics. The calculation methods are relatively mature and simple, which is conducive to more accurate center extraction and obtaining a more accurate clear position of Q' point.

[0125] In this embodiment, obtaining the top centroid position of the feature portion based on the first region of interest and the bottom centroid position of the reference portion based on the second region of interest includes: using the incident light spot 800s to scan the object 100 under test, and translating the incident light spot 800s relative to the object 100 under test, so as to obtain the detection image corresponding to the incident light spot 800s through the detector 810.

[0126] Specifically, in this embodiment, during the detection and scanning of the object under test using the incident light spot 800s, the first detector 820 and the second detector 830 are used to alternately image and scan the object under test 100, respectively acquiring the image information corresponding to the first detector 820 and the image information corresponding to the second detector 830.

[0127] In this embodiment, the top centroid position of the feature part is obtained based on the first region of interest of multiple detection images; the bottom centroid position of the reference part is obtained based on the second region of interest of multiple detection images.

[0128] Specifically, in this embodiment, obtaining the top centroid position of the feature portion based on the first region of interest of multiple detection images includes: obtaining a centroid position point cloud map and a grayscale sum point cloud map of the test object 100 based on the first region of interest and the second region of interest of multiple detection images. The centroid position point cloud map represents the correspondence between different positions on the surface of the test object 100 and the centroid position, and the grayscale sum point cloud map represents the correspondence between different positions on the surface of the test object 100 and the grayscale sum value. The top centroid position of the feature portion is obtained based on the centroid position point cloud map and the grayscale sum point cloud map.

[0129] The centroid position point cloud map shows the correspondence between different positions in the region of interest on the detector target surface and the centroid position, while the grayscale sum point cloud map shows the correspondence between different positions in the region of interest on the detector target surface and the grayscale sum value.

[0130] The centroid location point cloud map and the grayscale sum point cloud map are used as reference cloud maps for calculating the top and bottom centroid locations, and are uploaded to the server for subsequent calculations.

[0131] In this embodiment, the centroid position point cloud map and grayscale value point cloud map of the test object 100 are obtained based on the first and second regions of interest of multiple detection images. Data processing is performed on each image information, including: dividing the image information into multiple sub-image information columns along the scanning direction perpendicular to the detection scan; obtaining the spot centroid position of each sub-image information column in the first and second regions of interest, respectively, to form corresponding first and second point cloud vectors. The first point cloud vector represents the corresponding positional relationship between the spot centroid position in the first region of interest and the multiple sub-image information columns, and the second point cloud vector represents the corresponding positional relationship between the spot centroid position in the second region of interest and the multiple sub-image information columns; obtaining the grayscale value of each sub-image information column in the first and second regions of interest, respectively, to form corresponding third and fourth point cloud vectors. The third point cloud vector represents the corresponding positional relationship between the grayscale value in the first region of interest and the multiple sub-image information columns, and the fourth point cloud vector represents the corresponding positional relationship between the grayscale value in the second region of interest and the multiple sub-image information columns.

[0132] The image information is divided into multiple sub-image information columns along the scanning direction perpendicular to the detection scan. Each sub-image information column represents the position information along the scanning direction perpendicular to the detection scan.

[0133] The centroid position of the spot in each sub-image information column in the first region of interest and the second region of interest is obtained respectively. Specifically, the centroid position of the spot in each sub-image information column in the first region of interest represents the centroid position of the spot in the feature part, and the centroid position of the spot in each sub-image information column in the second region of interest represents the centroid position of the spot in the reference part.

[0134] The first point cloud vector represents the positional relationship between the centroid position of the spot in the first region of interest and the corresponding positional relationship between multiple sub-image information columns. The second point cloud vector represents the positional relationship between the centroid position of the spot in the second region of interest and the corresponding positional relationship between multiple sub-image information columns. Thus, the centroid position point cloud map corresponding to the entire test object 100 can be obtained based on the first and second point cloud vectors.

[0135] The third point cloud vector represents the corresponding positional relationship between the grayscale values ​​in the first region of interest and multiple sub-image information columns, and the fourth point cloud vector represents the corresponding positional relationship between the grayscale values ​​in the second region of interest and multiple sub-image information columns. Thus, the grayscale value point cloud map corresponding to the entire test object 100 can be obtained based on the third point cloud vector and the fourth point cloud vector.

[0136] As an example, the image information of m columns * n rows includes a first region of interest of [1:k] rows * m columns and a second region of interest of [k+1:n] rows * m columns. The image information is divided into multiple sub-image information columns, that is, the image information is divided into m columns. The centroid position and gray value of the spot in the first region of interest in each column are obtained as the first and second point cloud row vectors of 1 row * m columns. The centroid position and gray value of the spot in the second region of interest in each column are obtained as the third and fourth point cloud row vectors of 1 row * m columns. In other words, for each image information, 4 corresponding point cloud row vectors are obtained.

[0137] Accordingly, in this embodiment, the centroid position point cloud map of the sampling point is obtained based on the first point cloud vector and the second point cloud vector; the grayscale and value point cloud map of the sampling point is obtained based on the third point cloud vector and the fourth point cloud vector.

[0138] In this embodiment, obtaining the centroid position point cloud map of the sampling point based on the first point cloud row vector and the second point cloud row vector includes: for the same image information, when the centroid position of the spot in the first point cloud row vector is not 0, the centroid position of the first point cloud row vector is selected as the centroid position point cloud data; when the centroid position of the spot in the first point cloud row vector is 0, the centroid position of the spot at the corresponding position in the second point cloud row vector is selected as the centroid position point cloud data.

[0139] The first point cloud vector is the centroid position of the feature part of the light spot. Therefore, the first point cloud vector is used as the first selection. Only when the centroid position in the first point cloud vector is 0 is the centroid position in the second point cloud vector that is in the same image information column as it selected.

[0140] In this embodiment, the selected centroid location point cloud data is used to construct one-dimensional centroid location point cloud data based on the corresponding positions of multiple sub-image information columns.

[0141] As an example, for the first point cloud row vector with 1 row * m columns, when the centroid position in the first point cloud row vector is not 0, the centroid position in the first point cloud row vector remains unchanged. When the centroid position in the first point cloud row vector is 0, it is replaced with the centroid position of the same image information column in the second point cloud row vector, thus obtaining a one-dimensional centroid position point cloud data corresponding to the positions of multiple image information columns in the image information.

[0142] In this embodiment, one-dimensional centroid location point cloud data of multiple image information are stitched together along the scanning direction of the second detection scan to obtain a centroid location point cloud map.

[0143] By stitching together one-dimensional centroid location point cloud data from multiple image information along the scanning direction of the detection scan, a centroid location point cloud map representing the centroid location of 100 global sampling points of the object under test can be obtained.

[0144] Specifically, the one-dimensional centroid location point cloud data of multiple image information are alternately spliced ​​along the scanning direction of the detection scan according to the sampling order of the first detector 820 and the second detector 830.

[0145] In this embodiment, the grayscale and value point cloud map of the sampling points is obtained based on the image information. The grayscale and value point cloud map includes a first grayscale and value point cloud map corresponding to the first region of interest, and a total grayscale and value point cloud map corresponding to the first region of interest and the second region of interest.

[0146] The first grayscale sum point cloud map is used as a reference for obtaining the location of the feature part, and as a reference element for obtaining the location of the top centroid.

[0147] The total grayscale sum point cloud map is used as a reference for obtaining the location of the feature part and the location of the reference part.

[0148] In this embodiment, obtaining the grayscale and value point cloud map of the sampling points based on the third point cloud vector and the fourth point cloud vector includes: stitching the third point cloud vector along the scanning direction of the detection scan to obtain the first grayscale and value point cloud map.

[0149] By stitching together the third point cloud row vectors of multiple image information along the scanning direction of the detection scan, a first gray-level and value point cloud map representing the gray-level and value situation of the feature part can be obtained.

[0150] Specifically, the third point cloud vectors of multiple image information are alternately spliced ​​along the scanning direction of the detection scan according to the sampling order of the first detector 820 and the second detector 830.

[0151] In this embodiment, the third point cloud vector is added to the fourth cloud vector to obtain the fifth point cloud vector; the fifth point cloud vector is then stitched together along the scanning direction of the detection scan to obtain the total grayscale sum point cloud map.

[0152] By stitching together the fifth point cloud row vectors of multiple image information along the scanning direction of the detection scan, a total gray level and value point cloud map representing the gray level and value of the global feature parts of the object under test can be obtained.

[0153] Specifically, the fifth point cloud vectors of multiple image information are alternately spliced ​​along the scanning direction of the detection scan according to the sampling order of the first detector 820 and the second detector 830.

[0154] In this embodiment, the grayscale sum point cloud map also includes a second grayscale sum point cloud map corresponding to the second region of interest.

[0155] The second grayscale sum point cloud map is used as a reference for obtaining the position of the base part, and as a reference element for obtaining the position of the bottom centroid.

[0156] In this embodiment, obtaining the grayscale and value point cloud map of the sampling points based on the third point cloud vector and the fourth point cloud vector includes: stitching the fourth point cloud vector along the scanning direction of the detection scan to obtain the second grayscale and value point cloud map.

[0157] By stitching together the fourth point cloud row vectors of multiple image information along the scanning direction of the detection scan, a second gray-level and value point cloud map representing the gray-level and value situation of the reference part can be obtained.

[0158] Specifically, the fourth point cloud vectors of multiple image information are alternately spliced ​​along the scanning direction of the detection scan according to the sampling order of the first detector 820 and the second detector 830.

[0159] In this embodiment, obtaining the top centroid position of the feature based on the centroid position point cloud map and the grayscale sum point cloud map includes: determining the position of the feature based on the centroid position point cloud map.

[0160] The centroid position point cloud map represents the centroid position corresponding to the position of each point on the test object 100. The position of the feature part on the test object 100 can be determined by the distribution of the centroid position in the centroid position point cloud map.

[0161] In this embodiment, the location of the feature is determined by combining the total grayscale value point cloud map and the centroid location point cloud map.

[0162] The light intensity reflected by the feature part and the reference part after being illuminated by incident light is different, resulting in a significant difference in the total grayscale and value point cloud map. Therefore, combining the total grayscale and value point cloud map as an aid in determining the position of the feature part is beneficial for more accurate determination of the feature part's position.

[0163] In this embodiment, points in a first set region at the location of the feature part are obtained in the centroid location point cloud map, and points in a second set region at the location of the feature part are obtained in the grayscale sum point cloud map. The first set region and the second set region are the same size.

[0164] The points in the first set area around the location of the feature refer to the effective points around the location of the feature used for detecting the feature, that is, the points of the sampling spot obtained for multiple relative positions of the same feature during the scanning process.

[0165] The first grayscale sum point cloud map corresponds to the first region of interest, which is the feature part. Therefore, points in the same first set area around the position of the feature part are obtained in the centroid position point cloud map and the first grayscale sum point cloud map, respectively.

[0166] In this embodiment, the centroid position point cloud data corresponding to the points in the first set area is used as the top calculated point cloud data; the grayscale and value corresponding to the points in the second set area are used as the top calculated grayscale and value; and the top centroid position of the feature is obtained based on the top calculated point cloud data and the top calculated grayscale and value.

[0167] In other words, the top centroid position of the feature is obtained based on the centroid position and grayscale value in the same region.

[0168] In this embodiment, the point in the centroid location point cloud map is used as the first point, and the point in the first grayscale sum point cloud map is used as the second point.

[0169] In this embodiment, the top centroid position of the feature part is obtained based on the top measured point cloud data and the top measured gray sum value. This includes: taking the top measured gray sum value of each second point in the first set area of ​​the first gray sum value point cloud map as the weight of the top measured point cloud data of the first point at the corresponding position in the first set area of ​​the centroid position point cloud map, and performing weighted average processing on the top measured point cloud data to obtain the top centroid position.

[0170] The grayscale value can characterize the quality of the signal light of the obtained feature. The larger the grayscale value, the better the quality of the signal light of the feature. In other words, the better the imaging quality of the feature, the larger its proportion in the weighted average processing, thus enabling the acquisition of a more accurate weighted height.

[0171] Weighted averaging of the top measured point cloud data helps to comprehensively consider the imaging quality of feature parts at different relative positions, improves the accuracy of obtaining the top centroid position of the feature parts, and thus helps to obtain high-precision detection results.

[0172] By directly using the grayscale values ​​measured at the top as the weights corresponding to the top measured point cloud data, the weights are obtained more intuitively and the calculation method is simpler, while comprehensively considering the quality of signal light at different relative positions, which is conducive to the implementation of the detection method.

[0173] In other embodiments, the top centroid position of the feature portion can be obtained based on the top measured point cloud data and the top measured grayscale sum value, including: dividing the top measured point cloud data into multiple data columns along the scanning direction of the detection scan; using the top measured grayscale sum value of each second point in the first set area of ​​the first grayscale sum value point cloud map as the weight of the top measured point cloud data of the first point at the corresponding position in the first set area of ​​the centroid position point cloud map, performing weighted average processing on the top measured point cloud data in each data column to obtain multiple top centroid sub-positions; and obtaining the average value of the multiple top centroid sub-positions as the top centroid position.

[0174] For features with relatively flat tops, the average of multiple top centroid positions can be directly obtained as the top centroid position.

[0175] In other embodiments, the top centroid position of the feature portion can be obtained based on the top measured point cloud data and the top measured grayscale sum value, including: dividing the top measured point cloud data into multiple data columns along the scanning direction of the detection scan; using the top measured grayscale sum value of each second point in the first set area of ​​the first grayscale sum value point cloud map as the weight of the top measured point cloud data of the first point corresponding to the position in the first set area of ​​the centroid position point cloud map, performing weighted average processing on the top measured point cloud data in each data column to obtain multiple top centroid sub-positions; and performing fitting processing on the multiple top centroid sub-positions to obtain the contour curve corresponding to the feature portion, wherein the contour curve corresponds to the multiple top centroid positions of the feature portion.

[0176] For features with large surface undulations, there is no precise location to characterize the height of the feature. By using fitting processing, the contour curve of the top centroid position is obtained, thereby obtaining the distribution of the top centroid position of the feature surface. Subsequently, the height distribution of the feature surface is obtained, and then the height point that meets the requirements is selected from the height distribution according to actual needs.

[0177] In this embodiment, obtaining the bottom centroid position of the reference part based on multiple image information includes: determining the position of the reference part based on the second grayscale sum point cloud map.

[0178] The second grayscale sum point cloud map represents the grayscale sum corresponding to the reference part, thereby enabling the position of the reference part to be determined based on the second grayscale sum point cloud map.

[0179] In this embodiment, in the centroid position point cloud map, the centroid position point cloud data of the reference part is taken as the bottom calculated point cloud data; the average value of the bottom calculated point cloud data is taken as the bottom centroid position.

[0180] Typically, the surface of the object under test 100 is relatively flat, and the gray levels and values ​​of each reference part do not differ much. Therefore, the average value of the bottom point cloud data can be directly taken as the bottom centroid position.

[0181] Execution step S4: Obtain the measured height difference between the feature part and the reference part based on the first detection information and the second detection information.

[0182] In this embodiment, obtaining the measurement height difference between the feature portion and the reference portion based on the first detection information and the second detection information includes: obtaining the measurement height difference between the feature portion and the reference portion along the surface perpendicular to the surface of the object to be measured 100 based on the position difference between the top centroid position and the bottom centroid position.

[0183] By obtaining the positional difference between the top and bottom centroids, the measurement height of the feature can be obtained. This allows us to determine the height difference between the feature and the surface of the object under test 100, thus providing the actual height of the feature. This helps reduce detection errors caused by unevenness of the object under test 100 itself, thereby facilitating a more accurate measurement of the feature's height.

[0184] In this embodiment, the measured height of the feature portion is obtained based on the position difference between the top centroid position and the bottom centroid position, including: obtaining the pixel value corresponding to the position difference between the top centroid position and the bottom centroid position; and using the product of the pixel value and the height value corresponding to the unit pixel as the measured height difference between the feature portion and the reference portion.

[0185] By using the product of the pixel value and the height value corresponding to each pixel as the measured height difference between the feature part and the reference part, the pixel difference in the image information can be converted into the height value in three-dimensional measurement.

[0186] In this embodiment, after acquiring the image information corresponding to the incident light spot by collecting the signal light at each relative position through the detector, and before acquiring the top centroid position of the feature part and the bottom centroid position of the reference part based on multiple image information, the method further includes: performing noise reduction processing on the image information respectively.

[0187] Denoising image information helps to obtain more accurate image information and reduce the interference of image noise, which in turn facilitates the subsequent accurate acquisition of the height information corresponding to the feature parts.

[0188] In this embodiment, the denoising process for the image information further includes: performing median filtering on the image information to remove salt and pepper noise.

[0189] Median filtering is effective at removing salt-and-pepper noise (i.e., impulse noise). While removing noise, it can also protect the edges of the signal, preventing them from becoming blurred. In addition, the algorithm for median filtering is relatively simple and easy to implement in hardware.

[0190] In this embodiment, after acquiring the image information corresponding to the incident light spot by collecting signal light at each relative position through the detector, and before acquiring the top centroid position of the feature part and the bottom centroid position of the reference part based on multiple image information, the method further includes: performing threshold segmentation processing on the image information to set the gray value of points in the image information that have a gray value lower than a preset gray value to zero.

[0191] The sampling spots of each image information are not exactly the same, so the benchmark for threshold segmentation is different. Therefore, it is necessary to set grayscale thresholds for each image information. Grayscale threshold segmentation helps to filter out the sampling spots of stray light on the surface of the test object 100 more accurately and reduce the interference of stray light on the imaging of the feature area.

[0192] Accordingly, this embodiment also provides a detection system. (See reference) Figure 8 This is a functional block diagram of an embodiment of the detection system of the present invention.

[0193] The detection system 50 includes: a detection image acquisition module 501, used to acquire a detection image of the object to be tested; a region of interest acquisition module 502, used to acquire a first region of interest and a second region of interest of the detection image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; a detection information acquisition module 503, used to obtain first detection information of the feature portion based on the first region of interest and second detection information of the reference portion based on the second region of interest; and a measurement height difference acquisition module 504, used to obtain the measurement height difference between the feature portion and the reference portion based on the first detection information and the second detection information.

[0194] In this embodiment, optical detection is used to detect the height of the feature portion, and the reference portion on the surface of the object to be measured is used as the detection reference for detecting the height of the feature portion. That is, the measured height difference between the feature portion and the reference portion on the surface of the object to be measured is used as the height detection of the feature portion.

[0195] Specifically, the feature portion is the bump to be measured, and the reference portion is the wafer surface at the bottom of the bump to be measured. The detection method of this embodiment is used to measure the microscopic three-dimensional morphology of the height of the bump to be measured.

[0196] The detection image acquisition module 501 is used to acquire the detection image of the object to be tested.

[0197] The detection image is acquired to prepare for subsequent acquisition of image information of the feature area and the reference area.

[0198] In this embodiment, optical detection is adapted to form an incident light spot on the surface of the object to be tested with sampling points by incident light, and to collect signal light from the sampling points by a detector, so as to obtain the measurement height of the feature based on the signal light. The sampling points include the feature and the reference part.

[0199] Specifically, in this embodiment, acquiring the detection image of the object to be tested includes: forming an incident light spot on the surface of the object to be tested by incident light, and forming signal light by reflection from the surface of the object to be tested; and acquiring the detection image corresponding to the incident light spot by collecting the signal light through a detector.

[0200] In this embodiment, the optical detection method is suitable for scanning the object to be tested in order to obtain multiple detection images of the object.

[0201] In this embodiment, optical detection is suitable for scanning the object under test using an incident light spot.

[0202] Specifically, in this embodiment, the incident light is reflected on the surface of the object to be measured to form signal light, which forms a triangular optical path, thereby using the triangulation method to detect the height of the feature.

[0203] In other embodiments, a dispersive spectrometer or a confocal microscope may be used to detect the height.

[0204] For the optical inspection methods corresponding to the optical inspection system, please refer to the previous description of the inspection methods, which will not be repeated here.

[0205] This invention also provides a device that can implement the detection method provided in this invention through a program-based detection method. An optional hardware structure for the terminal device provided in this invention can be as follows: Figure 9 As shown, it includes: at least one processor 01, at least one communication interface 02, at least one memory 03, and at least one communication bus 04.

[0206] In this embodiment, the number of processor 01, communication interface 02, memory 03, and communication bus 04 is at least one, and the processor 01, communication interface 02, and memory 03 communicate with each other through communication bus 04. Communication interface 02 can be an interface of a communication module for network communication, such as the interface of a GSM module. Processor 01 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. Memory 03 may include high-speed RAM and may also include non-volatile memory (NVM), such as at least one disk storage device. Memory 03 stores one or more computer instructions, which are executed by processor 01 to implement the detection method provided in this embodiment of the present invention.

[0207] It should be noted that the aforementioned terminal device may also include other devices (not shown) that may not be essential to understanding the content disclosed in the embodiments of the present invention; given that these other devices may not be essential for understanding the content disclosed in the embodiments of the present invention, the embodiments of the present invention will not describe them one by one.

[0208] This invention also provides a storage medium storing one or more computer instructions, which are used to implement the detection method provided in this invention.

[0209] The embodiments of the present invention obtain first detection information of the feature part and second detection information of the reference part by acquiring the first region of interest and the second region of interest of the detection image, which is beneficial to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0210] The embodiments of the present invention described above are combinations of elements and features of the present invention. Unless otherwise stated, the elements or features described are optional. Individual elements or features may be practiced without combination with other elements or features. Furthermore, embodiments of the present invention may be constructed by combining some elements and / or features. The order of operations described in the embodiments of the present invention may be rearranged. Some constructions of any embodiment may be included in another embodiment and may be replaced by corresponding constructions of another embodiment. It will be apparent to those skilled in the art that claims in the appended claims that are not expressly referenced to each other may be combined to form embodiments of the present invention, or may be included as new claims in amendments made after the filing of this application.

[0211] Embodiments of the present invention can be implemented by various means, such as hardware, firmware, software, or combinations thereof. In a hardware configuration, the method according to an exemplary embodiment of the present invention can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc. In a firmware or software configuration, embodiments of the present invention can be implemented in the form of modules, processes, functions, etc. Software code can be stored in memory units and executed by a processor. The memory units are located inside or outside the processor and can send data to and receive data from the processor via various known means.

[0212] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is accorded the widest scope consistent with the principles and novel features disclosed herein.

[0213] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. An optical detection method, characterized in that, The method for detecting the height difference between a feature portion and a reference portion on the surface of an object to be measured includes: Incident light forms an incident light spot on the surface of the object under test, and the incident light is reflected by the surface of the object under test to form a signal light. The detector collects the signal light to obtain the detection image corresponding to the incident light spot. A first region of interest and a second region of interest are obtained from the detected image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; First detection information of the feature portion is obtained based on the first region of interest, and second detection information of the reference portion is obtained based on the second region of interest. The measured height difference between the feature portion and the reference portion is obtained based on the first detection information and the second detection information; The process of obtaining the first region of interest and the second region of interest of the detected image includes: Obtaining the optical parameter value distribution of the detected image includes: performing a one-dimensional projection of the image information of the detected image along a first direction to obtain first projection data, wherein the first projection data represents the correspondence between the position of each pixel point and the projection value in a second direction, and the projection value is the maximum value of the optical parameter value; the first direction is the row direction of the detector target surface, and the second direction is the column direction of the detector target surface; the optical parameter value distribution is the correspondence between the position of each pixel point in the detected image and the optical parameter value, wherein the optical parameter value includes grayscale value; Based on the detected image, a first region and a second region along the second direction are determined, wherein the first region includes image information of the feature portion and the second region includes image information of the reference portion; the peak position corresponding to the first projection data is obtained, including a first peak position corresponding to the first region and a second peak position corresponding to the second region; a first region of interest is obtained based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; a second region of interest is obtained based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position; Alternatively, obtaining the first region of interest and the second region of interest of the detected image includes: Obtaining the optical parameter value distribution of the detected image further includes: stitching together the first projection data corresponding to multiple detected images along the first direction to obtain a data matrix; The data matrix is ​​projected in one dimension along the first direction to obtain second projection data. The second projection data represents the correspondence between the positions of multiple pixels in the second direction and the projection values. The projection values ​​are the maximum, minimum, or average values ​​of the optical parameter values. The optical parameter value distribution is the correspondence between the positions of each pixel in the detection image and the optical parameter values. The optical parameter values ​​include grayscale values. Obtain the peak position corresponding to the second projection data, including a first peak position corresponding to the first region and a second peak position corresponding to the second region; obtain the first region of interest based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; obtain the second region of interest based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position.

2. The optical detection method as described in claim 1, characterized in that, The optical detection method is suitable for scanning the object to be tested to obtain multiple detection images of the object to be tested; The first direction is the scanning direction perpendicular to the detection scan, and the second direction is the scanning direction of the detection scan.

3. The optical detection method as described in claim 2, characterized in that, Obtaining the first region of interest based on the first peak position and obtaining the second region of interest based on the second peak position includes: obtaining a first location region corresponding to a point that is continuous with the first peak position and whose projection value is not 0, based on the first peak position; Based on the second peak position, obtain the second position region corresponding to the point that is continuous with the second peak position and whose projection value is not 0; Based on the first location region, a location range covering the first location region along the second direction is obtained as the first region of interest; Based on the second location region, the range of locations covering the second location region along the second direction is obtained as the second range of interest.

4. The optical detection method as described in claim 1, characterized in that, Obtaining first detection information of the feature portion based on the first region of interest, and obtaining second detection information of the reference portion based on the second region of interest, including: The top centroid position of the feature portion is obtained based on the first region of interest, and the bottom centroid position of the reference portion is obtained based on the second region of interest. Obtaining the measured height difference between the feature portion and the reference portion based on the first detection information and the second detection information includes: obtaining the measured height difference between the feature portion and the reference portion along a path perpendicular to the surface of the object under test based on the image position difference between the top centroid position and the bottom centroid position.

5. The optical detection method as described in claim 4, characterized in that, The optical detection is adapted to use an incident light spot to scan the object under test and acquire multiple detection images of the object under test; Obtaining the top centroid position of the feature portion based on the first region of interest and the bottom centroid position of the reference portion based on the second region of interest includes: using the incident light spot to scan the object under test, and translating the incident light spot relative to the object under test so as to obtain the detection image corresponding to the incident light spot through the detector. The top centroid position of the feature portion is obtained based on the first region of interest of the multiple detected images; The bottom centroid position of the reference part is obtained based on the second region of interest of the multiple detected images.

6. The optical detection method as described in claim 5, characterized in that, Obtaining the top centroid position of the feature based on the first region of interest of multiple detection images includes: obtaining a centroid position point cloud map and a grayscale sum point cloud map of the object under test based on the first region of interest and the second region of interest of multiple detection images, wherein the centroid position point cloud map represents the correspondence between different positions on the surface of the object under test and the centroid position, and the grayscale sum point cloud map represents the correspondence between different positions on the surface of the object under test and the grayscale sum value; The top centroid position of the feature is obtained based on the centroid position point cloud map and the grayscale sum point cloud map.

7. The optical detection method as described in claim 6, characterized in that, Obtaining the top centroid position of the feature based on the centroid position point cloud map and the grayscale sum point cloud map includes: determining the position of the feature based on the centroid position point cloud map; In the centroid location point cloud map, points in a first set region at the location of the feature are obtained, and in the grayscale sum point cloud map, points in a second set region at the location of the feature are obtained, wherein the first set region and the second set region are of the same size. Use the centroid location point cloud data corresponding to the points within the first defined area as the top calculated point cloud data; The grayscale and values ​​corresponding to the points within the second set area are used as the grayscale and values ​​of the top measurement. The top centroid position of the feature is obtained based on the top measured point cloud data and the top measured grayscale value.

8. The optical detection method as described in claim 4, characterized in that, Based on the image position difference between the top centroid position and the bottom centroid position, the measured height difference between the feature portion and the reference portion along the perpendicular to the surface of the object under test is obtained, including: obtaining the pixel value corresponding to the position difference between the top centroid position and the bottom centroid position; and using the product of the pixel value and the actual height value corresponding to the unit pixel as the measured height difference between the feature portion and the reference portion.

9. An optical detection system, characterized in that, The detection system is used to detect the height difference between a feature portion and a reference portion on the surface of an object to be measured, and includes: The detection image acquisition module is used to form an incident light spot on the surface of the object under test by incident light, and to form a signal light by reflection from the surface of the object under test. The detector collects the signal light to obtain the detection image corresponding to the incident light spot. The region of interest acquisition module is used to acquire a first region of interest and a second region of interest of the detected image, wherein the first region of interest includes image information of the feature portion and the second region of interest includes image information of the reference portion; The detection information acquisition module is used to obtain first detection information of the feature portion based on the first region of interest, and to obtain second detection information of the reference portion based on the second region of interest. A height difference acquisition module is used to obtain the height difference between the feature portion and the reference portion based on the first detection information and the second detection information. The process of obtaining the first region of interest and the second region of interest of the detected image includes: Obtaining the optical parameter value distribution of the detected image includes: performing a one-dimensional projection of the image information of the detected image along a first direction to obtain first projection data, wherein the first projection data represents the correspondence between the position of each pixel point and the projection value in a second direction, and the projection value is the maximum value of the optical parameter value; the first direction is the row direction of the detector target surface, and the second direction is the column direction of the detector target surface; the optical parameter value distribution is the correspondence between the position of each pixel point in the detected image and the optical parameter value, wherein the optical parameter value includes grayscale value; Based on the detected image, a first region and a second region along the second direction are determined, wherein the first region includes image information of the feature portion and the second region includes image information of the reference portion; the peak position corresponding to the first projection data is obtained, including a first peak position corresponding to the first region and a second peak position corresponding to the second region; a first region of interest is obtained based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; a second region of interest is obtained based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position; Alternatively, obtaining the first region of interest and the second region of interest of the detected image includes: Obtaining the optical parameter value distribution of the detected image further includes: stitching together the first projection data corresponding to multiple detected images along the first direction to obtain a data matrix; The data matrix is ​​projected in one dimension along the first direction to obtain second projection data. The second projection data represents the correspondence between the positions of multiple pixels in the second direction and the projection values. The projection values ​​are the maximum, minimum, or average values ​​of the optical parameter values. The optical parameter value distribution is the correspondence between the positions of each pixel in the detection image and the optical parameter values. The optical parameter values ​​include grayscale values. Obtain the peak position corresponding to the second projection data, including a first peak position corresponding to the first region and a second peak position corresponding to the second region; obtain the first region of interest based on the first peak position, wherein the boundary of the first region of interest along the second direction is located on both sides of the first peak position; obtain the second region of interest based on the second peak position, wherein the boundary of the second region of interest along the second direction is located on both sides of the second peak position.

10. A device, characterized in that, It includes at least one memory and at least one processor, the memory storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the detection method as described in any one of claims 1-8.

11. A storage medium, characterized in that, The storage medium stores one or more computer instructions, which are used to implement the detection method as described in any one of claims 1-8.

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