Optical detection method and system, equipment and storage medium

Abstract

An optical detection method, system and device and a storage medium are used for detecting a measurement height difference between a feature part and a reference part of the surface of an object to be detected, and the method comprises the following steps: obtaining a detection image of the object to be detected; a first region of interest and a second region of interest of the detection image are obtained, the first region of interest comprises image information of the feature part, and the second region of interest comprises image information of the reference part; obtaining first detection information of the feature part according to the first region of interest, and obtaining second detection information of the reference part according to the second region of interest; a measurement height difference between the feature portion and the reference portion is obtained based on the first detection information and the second detection information. According to the invention, accurate detection information can be obtained, the computing power is saved, the detection efficiency is improved, and high-stability and high-precision optical detection is realized.

Description

Technical Field

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

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

[0004] Currently, optical detection methods are usually 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 and system, equipment and storage medium to achieve high-stability and high-precision optical detection.

[0006] To solve the above problems, an embodiment of the present invention provides an optical detection method for detecting a measured height difference between a characteristic portion and a reference portion on the surface of an object to be detected, the detection method comprising: acquiring a detection image of the object to be detected; acquiring a first region of interest and a second region of interest of the detection image, the first region of interest including image information of the characteristic portion, and the second region of interest including image information of the reference portion; obtaining first detection information of the characteristic 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 measured height difference between the characteristic portion and the reference portion based on the first detection information and the second detection information.

[0007] An embodiment of the present invention also provides an optical detection system for detecting a measured height difference between a characteristic portion and a reference portion on the surface of an object to be detected, the detection system comprising: a detection image acquisition module, for acquiring a detection image of the object to be detected; an area of ​​interest acquisition module, for acquiring a first area of ​​interest and a second area of ​​interest of the detection image, the first area of ​​interest including image information of the characteristic portion, and the second area of ​​interest including image information of the reference portion; a detection information acquisition module, for obtaining first detection information of the characteristic portion based on the first area of ​​interest, and obtaining second detection information of the reference portion based on the second area of ​​interest; and a measurement height difference acquisition module, for obtaining a measured height difference between the characteristic portion and the reference portion based on the first detection information and the second detection information.

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

[0009] In the optical detection method provided by the embodiment of the present invention, a first region of interest and a second region of interest of a detection image are obtained, the first region of interest includes image information of a characteristic portion, the second region of interest includes image information of a reference portion, first detection information of the characteristic portion is obtained based on the first region of interest, second detection information of the reference portion is obtained based on the second region of interest, and a measured height difference between the characteristic portion and the reference portion is obtained based on the first detection information and the second detection information. The embodiment of the present invention obtains the first detection information of the characteristic portion and the second detection information of the reference portion by acquiring the first region of interest and the second region of interest of the detection image, respectively, which is conducive to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of an embodiment of a detection method of the present invention;

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

[0012] Figure 4 yes Figure 3 A local magnified image of any convex point to be tested;

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

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

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

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

[0017] Fig. 9 It is a hardware structure diagram of an embodiment of the device provided by the present invention. DETAILED DESCRIPTION

[0018] As can be seen from the background technology, optical detection method is a commonly used detection technology for characteristic parts on the object to be detected. However, in the existing optical detection methods used for detection, the accuracy of the detection results needs to be improved, and a better optical detection parameter setting method is needed to achieve high stability and high precision optical detection.

[0019] In order to solve the technical problem, an embodiment of the present invention provides an optical detection method for detecting a measured height difference between a characteristic part and a reference part on the surface of an object to be detected, the detection method comprising: acquiring a detection image of the object to be detected; acquiring a first region of interest and a second region of interest of the detection image, the first region of interest including image information of the characteristic part, and the second region of interest including image information of the reference part; obtaining first detection information of the characteristic part based on the first region of interest, and obtaining second detection information of the reference part based on the second region of interest; and obtaining the measured height difference between the characteristic part and the reference part based on the first detection information and the second detection information.

[0020] The embodiment of the present invention obtains the first region of interest and the second region of interest of the detection image to respectively obtain the first detection information of the characteristic part and the second detection information of the reference part, which is conducive to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0021] In order to make the above-mentioned purposes, features and advantages of the embodiments of the present invention more obvious and understandable, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0022] refer to Figure 1 , Figure 1 It is a flow chart 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 a detection image of the object to be detected, where the detection image includes image information of the object to be detected;

[0025] Step S2: 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 characteristic portion, and the second region of interest includes image information of the reference portion;

[0026] Step S3: obtaining first detection information of the characteristic part according to the first region of interest, and obtaining second detection information of the reference part according to the second region of interest;

[0027] Step S4: obtaining a measured height difference between the feature portion and the reference portion according to the first detection information and the second detection information.

[0028] The embodiment of the present invention obtains the first region of interest and the second region of interest of the detection image to respectively obtain the first detection information of the characteristic part and the second detection information of the reference part, which is conducive 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 describes each step of the detection method in conjunction with the detection system.

[0030] Combined with reference Figures 2 to 7 , Figure 2 and Figure 3 is a schematic diagram of a detection device and a light path diagram corresponding to an embodiment of a detection method of the present invention, Figure 4 yes Figure 3 A local enlarged view of any bump to be tested. Figure 5 is a top view of a detection device corresponding to an embodiment of a detection method of the present invention, Figure 6 is a schematic diagram of an embodiment of a one-dimensional projection, Figure 7 FIG. 1 is a schematic diagram of an embodiment of obtaining the first region of interest and the second region of interest. The detection method described in this embodiment is described in detail.

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

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

[0033] Execute step S1: obtain a detection image of the object to be detected 100.

[0034] The detection image is obtained to prepare for the subsequent acquisition of image information of the characteristic part and the reference part.

[0035] In this embodiment, the optical detection is suitable for forming an incident light spot 800s (such as Figure 5 As shown), the detector 810 collects signal light from the sampling point to obtain the measured height of the characteristic part according to the signal light, and the sampling point includes the characteristic part and the reference part.

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

[0037] In this embodiment, the optical detection method is suitable for performing detection scanning on the object to be detected 100 to obtain a plurality of detection images of the object to be detected 100 .

[0038] In this embodiment, the optical detection is suitable for performing detection scanning on the object to be detected 100 using the incident light spot 800s.

[0039] Specifically, in this embodiment, the incident light is reflected on the surface of the object to be measured 100 to form a signal light, forming a triangular optical path, so that the height of the characteristic part is detected by using the triangulation method.

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

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

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

[0043] This embodiment can obtain the measured height difference between the characteristic portion and the reference portion by optically detecting the sampling points, thereby obtaining the actual measured height of the characteristic portion.

[0044] In this embodiment, the detection image of the object to be detected 100 is obtained by the detector 810, and the detector 810 includes a first detector 820 and a second detector 830 (such as Figure 3 shown).

[0045] In this embodiment, the two detectors 810 work alternately to respectively collect imaging information of the incident light spot 810s and the incident light spot 820s until the linear scan of the object to be detected is completed, which is beneficial to improving the detection efficiency.

[0046] In other embodiments, the detector may also include only one detector (eg Figure 2 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 object to be tested 100 being blocked by flexibly adjusting the incident angle of the incident light, so that the feature portion can obtain more sufficient illumination, thereby facilitating more accurate imaging of the feature portion. The incident angle of the incident light is greater than 45 degrees, which is beneficial to increase the space above the object to be tested 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 is mirror-reflected by the surface of the object to be tested 100, and 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 to 35 degrees. This ensures that the characteristic portion can be more fully illuminated, and is conducive to facilitating the setting of the relative positions of the lighting module and the imaging module in the detection equipment, and is also conducive to the complete reception of the signal light by the imaging module, thereby facilitating more accurate imaging in the imaging module.

[0051] In this embodiment, the incident light spot 800s is in a strip shape, so that the detection device can be used to perform linear scanning on the object to be detected 100. In other embodiments, the incident light spot can also be a point light spot or a regional light spot.

[0052] The object to be measured 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 just butted against or partially overlapped. The linear incident light spots 800s are used to complete the linear scanning, which is beneficial to achieving full coverage of the object to be measured 100 by all linear incident light spots 800s. At the same time, each linear incident light spot 800s can be fully utilized, and a smaller number of linear incident light spots 800s can be used to complete the scanning of the object to be measured 100, thereby helping to improve the scanning efficiency.

[0053] Specifically, in conjunction with reference Figure 2 and Figure 3 The detection device used in the detection method includes a lighting module, the lighting module includes a light path transmission direction (such as Figure 2 and Figure 3 The light source assembly 200, the first slit element 400 and the first lens group 500 are sequentially arranged (as shown by the direction of the arrow on the dotted line), 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 to generate a linear incident light, and the first lens group 500 is used to focus the linear incident light onto the object to be measured 100 to generate a strip-shaped incident light spot 800s.

[0054] In this embodiment, along the transmission direction of the optical path, the light beam generated by the light source assembly 200 passes through the first slit element 400, thereby generating an incident light spot 800s on the object to be measured 100. Therefore, compared with a circular light beam, the light source assembly 200 generates a linear light beam. When the light beam generated by the light source assembly 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. The shaping element 220 is used to shape the light emitted by the light source to generate a linear light beam.

[0056] The light source in this embodiment is an incoherent light source. Compared with a coherent light source (for example, a laser light source), an incoherent light source has smaller noise points. Therefore, the light beam generated by the incoherent light source ultimately has a higher image signal-to-noise ratio in the imaging module, thereby being able to obtain more accurate imaging information of the characteristic parts in the imaging module.

[0057] Specifically, in this embodiment, the types of light sources include LED light sources, halogen lamps or xenon lamps.

[0058] In practical applications, an incoherent light source usually emits a circular light beam. Therefore, the shaping element 220 is used to shape the light emitted by the light source to ensure that the light source assembly 200 generates a linear light beam.

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

[0060] The use of an optical fiber bundle to shape the light emitted by a light source is simple and easy to operate, and the port shape of the optical fiber bundle is easy to adjust, so that the incident port of the optical fiber bundle can be adjusted according to the light spot formation of the light emitted by the light source, and the exit port of the optical fiber bundle can be adjusted according to the shape of the incident light to be obtained.

[0061] In this embodiment, the shape of the incident port of the optical fiber bundle matches the spot shape of the light emitted by the light source, thereby improving the coupling efficiency between the light emitted by the light source and the optical fiber bundle. The shape of the output port of the optical fiber bundle is in a straight line, thereby enabling the light source assembly 200 to generate a linear light 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 is used to control the spectrum emitted by the light box 210 .

[0064] The light box 210 is used as a device for placing a light source and a filter color wheel.

[0065] As an example, the light source emits white light, and after passing through the filter color wheel, the light box 210 can 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 part, for example, according to the spectrum of the coating on the surface of the wafer. Specifically, the spectrum of the filter color wheel is consistent with the spectrum of the surface coating of the feature part, which is conducive to improving the signal-to-noise ratio of the signal light generated by the incident light on the surface of the feature part.

[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 optical path of the incident light, so that linear incident light matching the slit opening can be obtained. Accordingly, in this embodiment, the length of the linear incident light obtained is controlled by setting the slit opening length of the first slit element 400.

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

[0069] In this embodiment, the size and spacing of the bumps to be tested are usually small, so 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 first slit element 400 and image it on the object to be tested 100, thereby reducing the width of the linear incident light passing through the first slit element 400, so that an incident light spot 800s with a smaller width can be obtained. When the incident light spot 800s is used to perform a linear scan on the object to be tested 100, it is beneficial to improve the scanning accuracy, thereby improving the accuracy of the detection result.

[0071] In this embodiment, the first slit element 400 and the first lens group 500 are used to shape and image the light beam generated by the light source assembly 200. The first lens group 500 can be used to reduce the first slit element 400 and image it on the object to be tested 100, so that a smaller incident light spot 800s can be obtained. The incident light spot 800s forms signal light through the object to be tested 100, which is conducive to obtaining higher-precision imaging information and correspondingly obtaining high-stability and high-precision detection results.

[0072] In this embodiment, the lighting module further includes: a fiber coupler 300 disposed between the light source assembly 200 and the first slit element 400 , and the 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 assembly 200 generates a linear light beam through an optical fiber bundle, and the light beam generated by the optical fiber bundle is a discontinuous light spot. Therefore, the optical fiber coupler 300 is used to converge the light beam and couple it at the slit opening of the first slit element 400, which is beneficial to improve the lighting efficiency of the incident light, control the light of the incident light, reduce the divergence of the incident light, and help improve the uniformity of imaging in the imaging module.

[0074] In this embodiment, the optical fiber coupler 300 includes: a cylindrical mirror 310, which is arranged on a side of the optical fiber coupler 300 close to the light emitting end face, or arranged on a side of the optical fiber coupler 300 close to the light incident end face.

[0075] The cylindrical mirror 310 is used to improve the lighting efficiency and uniformity of the incident light.

[0076] Execute step S2: acquire a first region of interest (ROI) and a second region of interest of the detection image, wherein the first region of interest includes image information of the characteristic portion, and the second region of interest includes image information of the reference portion.

[0077] The first region of interest is the region for detecting the characteristic part, and the second region of interest is the region for detecting the reference part. The first region of interest for the characteristic part and the second region of interest for the reference part are obtained respectively to obtain relatively accurate imaging areas of the characteristic part and the reference part. The detection calculations for the characteristic part and the reference part are performed separately, which is beneficial to improving the detection efficiency and the detection accuracy at the same time.

[0078] In this embodiment, obtaining the first region of interest and the second region of interest of the detection image includes: obtaining the light parameter value distribution of the detection image, the light parameter value distribution is the correspondence between the position of each pixel point in the detection image and the light parameter value, wherein the light parameter value includes a grayscale value.

[0079] The light parameter value distribution is the correspondence between the position of each pixel point in the detection image and the light parameter value. The light parameter value distribution can be used to obtain the imaging conditions of each position on the detection image, thereby obtaining the ROI area corresponding to the sampling point, wherein the light parameter value may include a grayscale value.

[0080] Correspondingly, in this embodiment, the first region of interest and the second region of interest of the detection image are obtained according to the distribution of light parameter values.

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

[0082] The image information can characterize the light parameter values ​​corresponding to each position on the target surface 80. The detector 810 collects signal light to obtain image information corresponding to the incident light spot 800s, so that the distribution of light parameter values ​​corresponding to each position on the target surface 80 can be obtained through the image information.

[0083] In this embodiment, taking the light parameter value as a grayscale value as an example, the obtained image information is an m-column*n-row grayscale value matrix corresponding to the position of each point on the object to be measured 100, that is, an m-column*n-row grayscale value matrix corresponding to each pixel point in the ROI.

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

[0085] In this embodiment, at least part of the signal light is collected by the detector 810, and imaging information of the sampling point is acquired according to the collected signal light, and the imaging information includes the spot 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, so that the setting of the target surface 80 in this embodiment is relatively simple and the modification of the original detection system is reduced.

[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 the detector 810 respectively, and each detector 810 collects each signal light in turn to form an image of different areas of the object to be tested 100.

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

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

[0090] In this embodiment, the second lens group 620 is used to amplify the optical path of the signal light, so that the imaging of the characteristic portion is clearer. As an example, the second lens group 620 is a second microscope objective lens.

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

[0092] In this embodiment, the aperture 630 images the characteristic portion at infinity, and the tube lens 640 is used to image the characteristic portion at a finite distance. Correspondingly, it is used to image the characteristic portion on the detector 810. The use of the aperture 630 and the tube lens 640 in combination is beneficial to ensure that the imaging quality of the signal light on the detector 810 is uniform, clear and accurate after passing through the imaging component 600.

[0093] In this embodiment, the imaging assembly 600 further includes: a second slit element 610 disposed on a side of the second lens group 620 facing away from the aperture 630 , and 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 and reduce the divergence of the signal light.

[0095] In this embodiment, the light parameter value distribution of the sampling points is obtained according to the light parameter value of each point in the image information.

[0096] In this embodiment, the detector 810 collects signal lights 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 relative to the object to be measured 100, so as to obtain image information of each sampling point.

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

[0099] Specifically, in this embodiment, the first direction is a scanning direction perpendicular to the detection scan, and the second direction is a scanning direction perpendicular to the detection scan (eg Figure 5 X direction).

[0100] In this embodiment, the light parameter value is taken as a gray value. Figure 6 As shown, a one-dimensional projection is performed on any image information along a 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 of m columns*n rows is obtained along the scanning direction perpendicular to the detection scan, and the first projection column vector 1*n is the maximum value of the gray value of each row in the gray value matrix of m columns*n rows.

[0101] In this embodiment, obtaining the light parameter value distribution of the detection image further includes: splicing the first projection data corresponding to the plurality of detection images along the first direction to obtain a data matrix.

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

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

[0104] In this embodiment, a one-dimensional projection is performed on the data matrix along the first direction to obtain second projection data, which represents the correspondence between the positions of multiple pixel points in the second direction and the projection values, and the projection values ​​are the maximum, minimum or mean values ​​of the light parameter values.

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

[0106] The second projection column vector 1*n is a grayscale value representation obtained according to the image grayscale value distribution of the object 100 after the object 100 is completely scanned. The grayscale value in the second projection data can be used to represent the grayscale value distribution at different positions along the scanning direction perpendicular to the detection scan, so that the positions of different categories of sampling points along the scanning direction perpendicular to the detection scan can be judged according to the grayscale value distribution. According to the global grayscale value distribution, the representation of the second projection data is beneficial to be more accurate.

[0107] In this embodiment, obtaining a first region of interest and a second region of interest according to the distribution of light parameter values ​​includes: obtaining 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; obtaining the first region of interest according to the first peak position, and the boundaries of the first region of interest along the second direction are located on both sides of the first peak position; obtaining the second region of interest according to the second peak position, and the boundaries of the second region of interest along the second direction are located on both sides of the second peak position.

[0108] The peak position of the second projection data can represent a point on the object to be measured 100 where the incident light is better reflected, wherein 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 characteristic portion and the reference portion can be located by the peak position, so that the peak position corresponds to the region of interest one-to-one, and the boundaries of the region of interest are located on both sides of the peak position, so that the region of interest includes all signal light reflected by the incident light in the sampling point area.

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

[0110] In this embodiment, obtaining a first region of interest according to a first peak position and obtaining a second region of interest according to a second peak position include: according to the first peak position, obtaining a first position region of points that are continuous with the first peak position and whose projection values ​​are not 0; according to the second peak position, obtaining a second position region corresponding to points that are continuous with the second peak position and whose projection values ​​are not 0; according to the first position region, obtaining a position range covering the first position region along a second direction as the first region of interest; according to the second position region, obtaining a position range covering the second position region along a second direction as the second range of interest.

[0111] like Figure 7 As shown, taking the second projection data as the average value as an example, the first position area of ​​the points that are continuous with the first peak position and whose projection values ​​are not 0 is obtained, that is, the area of ​​the signal light reflected by the incident light in the characteristic area, so that the first area of ​​interest covers the first position area, which is beneficial to ensure that all effective areas for detecting the characteristic parts are detected.

[0112] like Figure 7 As shown, taking the second projection data as an average value as an example, a second position area of ​​points that are continuous with the second peak position and whose projection values ​​are not 0 is obtained, that is, the area of ​​signal light reflected by the incident light in the reference part area, so that the second area of ​​interest covers the second position area, which is beneficial to ensure that all effective areas used to detect the reference part are detected.

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

[0114] In other embodiments, acquiring the first region of interest and the second region of interest based on the distribution of light parameter values ​​may also include: determining the first region and the second region included along the second direction based on the detection image, wherein the first region includes image information of the characteristic portion, and the second region includes image information of the reference portion; acquiring 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; acquiring the first region of interest based on the first peak position, wherein the boundaries of the first region of interest along the second direction are located on both sides of the first peak position; acquiring the second region of interest based on the second peak position, wherein the boundaries of the second region of interest along the second direction are located on both sides of the second peak position.

[0115] Execute step S3: obtain first detection information of the characteristic part according to the first region of interest, and obtain second detection information of the reference part according to the second region of interest.

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

[0117] This embodiment obtains the first region of interest and the second region of interest of the detection image to obtain the first detection information of the characteristic part and the second detection information of the reference part respectively, which is conducive to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0118] In this embodiment, first detection information of the characteristic part is obtained according to the first region of interest, and second detection information of the reference part is obtained according to the second region of interest, including: obtaining the top center of mass position of the characteristic part according to the first region of interest, and obtaining the bottom center of mass position of the reference part according to the second region of interest.

[0119] The top centroid location and the bottom centroid location 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. Figure 4 A partial enlarged view of any bump to be tested is shown for ease of explanation. Figure 4 In the figure, two convex points to be tested with different heights overlap, wherein a black solid convex point is used to represent the first convex point to be tested 101a, and a dotted outline is used to represent the second convex point to be tested 101b. For the first convex point to be tested 101a, when the incident light is irradiated on the first convex point to be tested 101a, it is reflected by point P to form a signal light (the optical path of the signal light formed by the reflection of point P is represented by a dotted line), and the imaging spot on the target surface 80 is at point P'. For the second convex point to be tested 101b, when the incident light is irradiated on the second convex point to be tested 101b, it is reflected by point Q to form a signal light (the optical path of the signal light formed by the reflection of point P is represented by a solid line), and the imaging spot on the target surface 80 is 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, and 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 mirror reflected, then the incident light and the signal light are not perpendicular, therefore, the base surface 80e and the optical axis 10a of the incident light do not coincide, that is, point Q on the second convex point 101b to be measured is not on the base surface 80e, so that the imaging spot of the incident light passing through point Q is a diffuse spot, that is, point Q cannot be clearly imaged at point Q', but forms a diffuse spot at point Q', therefore, in order to obtain a clear position of point Q', the diffuse spot also needs to be processed.

[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 the Q' point, that is, the centroid position.

[0123] In this embodiment, the method for center extraction includes grayscale centroid method, quadratic curve fitting vertex method, Gaussian curve fitting vertex method, centroid method or maximum value position method.

[0124] Grayscale centroid method, quadratic curve fitting vertex method, Gaussian curve fitting vertex method, centroid method or maximum 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 and clear position of the Q' point.

[0125] In this embodiment, the top centroid position of the characteristic part is obtained according to the first region of interest, and the bottom centroid position of the reference part is obtained according to the second region of interest, including: using the incident light spot 800s to detect and scan the object to be tested 100, so that the incident light spot 800s and the object to be tested 100 are relatively translated to obtain a detection image corresponding to the incident light spot 800s through the detector 810.

[0126] Specifically, in this embodiment, the incident light spot 800s is used to detect and scan the object to be tested, and the first detector 820 and the second detector 830 are used to alternately image the object to be tested 100 for detection and scanning, and image information corresponding to the first detector 820 and image information corresponding to the second detector 830 are respectively obtained.

[0127] In this embodiment, the top centroid position of the feature part is acquired according to the first region of interest of the plurality of detection images; and the bottom centroid position of the reference part is acquired according to the second region of interest of the plurality of detection images.

[0128] Specifically, in this embodiment, the top centroid position of the characteristic part is obtained according to the first region of interest of multiple detection images, including: obtaining a centroid position point cloud map and a grayscale sum value point cloud map of the object to be tested 100 according to the first region of interest and the second region of interest of multiple detection images, the centroid position point cloud map is the correspondence between different positions on the surface of the object to be tested 100 and the centroid position, and the grayscale sum value point cloud map is the correspondence between different positions on the surface of the object to be tested 100 and the grayscale sum value; according to the centroid position point cloud map and the grayscale sum value point cloud map, the top centroid position of the characteristic part is obtained.

[0129] The centroid position point cloud is the correspondence between different positions in the detector target surface area of ​​interest and the centroid position, and the grayscale and value point cloud is the correspondence between different positions in the detector target surface area of ​​interest and the grayscale and value.

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

[0131] In this embodiment, a point cloud image of the centroid position and a point cloud image of the grayscale sum value of the object to be tested 100 are obtained according to the first region of interest and the second region of interest of the plurality of detection images: data processing is performed on each image information, and the data processing includes: dividing the image information into a plurality of sub-image information columns along a scanning direction perpendicular to the detection scan; obtaining the centroid position of the light spot of each sub-image information column in the first region of interest and the second region of interest respectively, forming a corresponding first point cloud row vector and a second point cloud row vector, the first point cloud row vector represents the corresponding position relationship between the centroid position of the light spot in the first region of interest and the plurality of sub-image information columns, and the second point cloud row vector represents the corresponding position relationship between the centroid position of the light spot in the second region of interest and the plurality of sub-image information columns; obtaining the grayscale sum of each sub-image information column in the first region of interest and the second region of interest respectively, forming a corresponding third point cloud row vector and a fourth point cloud row vector, the third point cloud row vector represents the corresponding position relationship between the grayscale sum value and the plurality of sub-image information columns in the first region of interest, and the fourth point cloud row vector represents the corresponding position relationship between the grayscale sum value and the plurality of sub-image information columns in the second region of interest.

[0132] The image information is divided into a plurality of sub-image information columns along a scanning direction perpendicular to the detection scanning, and each sub-image information column corresponds to position information along the scanning direction perpendicular to the detection scanning.

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

[0134] The first point cloud row vector represents the corresponding position relationship between the centroid position of the light spot in the first area of ​​interest and the multiple sub-image information columns, and the second point cloud row vector represents the corresponding position relationship between the centroid position of the light spot in the second area of ​​interest and the multiple sub-image information columns, so that a point cloud map corresponding to the global centroid position of the object to be tested 100 can be obtained based on the first point cloud row vector and the second point cloud row vector.

[0135] The third point cloud row vector represents the corresponding position relationship between the grayscale sum value and the multiple sub-image information columns in the first region of interest, and the fourth point cloud row vector represents the corresponding position relationship between the grayscale sum value and the multiple sub-image information columns in the second region of interest, so that the grayscale and value point cloud map corresponding to the global object 100 can be obtained according to the third point cloud row vector and the fourth point cloud row vector.

[0136] As an example, 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, and the centroid position and grayscale sum value of the first region of interest in each column are obtained as the first point cloud row vector and the second point cloud row vector of 1 row*m columns, and the centroid position and grayscale sum value of the second region of interest in each column are obtained as the third point cloud row vector and the fourth point cloud row vector of 1 row*m columns. That is to say, for each image information, 4 corresponding point cloud row vectors are obtained.

[0137] Correspondingly, in this embodiment, a point cloud image of the centroid position of the sampling point is obtained according to the first point cloud row vector and the second point cloud row vector; and a point cloud image of the grayscale and value of the sampling point is obtained according to the third point cloud row vector and the fourth point cloud row vector.

[0138] In this embodiment, a point cloud image of the centroid position of the sampling point is obtained according to the first point cloud row vector and the second point cloud row vector, including: for the same image information, when the centroid position of the light 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 light spot in the first point cloud row vector is 0, the centroid position of the light 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 row vector is the centroid position of the light spot of the feature part, so the first point cloud row vector is selected as the first choice. When the centroid position in the first point cloud row vector is 0, the centroid position in the same image information column in the second point cloud row vector is selected.

[0140] In this embodiment, the selected centroid position point cloud data is formed into one-dimensional centroid position point cloud data according to the corresponding positions of a plurality of sub-image information columns.

[0141] As an example, for the first point cloud row vector of 1 row * m columns, when the center of mass position in the first point cloud row vector is not 0, the center of mass position in the first point cloud row vector is kept unchanged; when the center of mass position in the first point cloud row vector is 0, it is replaced by the center of mass position of the same image information column in the second point cloud row vector, and a one-dimensional center of mass position point cloud data corresponding to the positions of multiple image information columns in the image information is obtained.

[0142] In this embodiment, the one-dimensional centroid position point cloud data of the plurality of image information are spliced ​​along the scanning direction of the second detection scan to obtain a centroid position point cloud map.

[0143] The one-dimensional centroid position point cloud data of the multiple image information are spliced ​​along the scanning direction of the detection scan, so as to obtain a centroid position point cloud image representing the centroid position of the global sampling points of the object to be tested 100.

[0144] Specifically, the one-dimensional centroid position point cloud data of the plurality of image information are spliced ​​alternately 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 according to the image information, and 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 and value point cloud image is used as a reference for obtaining the position of the feature part and as a reference element for obtaining the top centroid position.

[0147] The total grayscale and value point cloud images are used as a reference for obtaining the position of the feature part and the reference for obtaining the position of the reference part.

[0148] In this embodiment, the grayscale and value point cloud map of the sampling point is obtained according to the third point cloud row vector and the fourth point cloud row vector, including: splicing the third point cloud row vector along the scanning direction of the detection scan to obtain the first grayscale and value point cloud map.

[0149] The third point cloud row vectors of the plurality of image information are spliced ​​along the scanning direction of the detection scan, so as to obtain a first grayscale and value point cloud image representing the grayscale and value of the characteristic portion.

[0150] Specifically, the third point cloud row vectors of the plurality of image information are spliced ​​alternately 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 row vector is added to the fourth cloud row vector to obtain a fifth point cloud row vector; the fifth point cloud row vector is spliced ​​along the scanning direction of the detection scan to obtain a total grayscale and value point cloud map.

[0152] The fifth point cloud row vectors of the multiple image information are spliced ​​along the scanning direction of the detection scan, so as to obtain a total grayscale and value point cloud image representing the grayscale and value conditions of the global characteristic parts of the object to be tested 100.

[0153] Specifically, the fifth point cloud row vectors of the plurality of image information are spliced ​​alternately 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 and value point cloud map further includes a second grayscale and value point cloud map corresponding to the second region of interest.

[0155] The second grayscale and value point cloud image is used as a reference for obtaining the position of the reference portion and as a reference element for obtaining the position of the bottom centroid.

[0156] In this embodiment, the grayscale and value point cloud map of the sampling point is obtained according to the third point cloud row vector and the fourth point cloud row vector, including: splicing the fourth point cloud row vector along the scanning direction of the detection scan to obtain the second grayscale and value point cloud map.

[0157] The fourth point cloud row vectors of the plurality of image information are spliced ​​along the scanning direction of the detection scan, so as to obtain a second grayscale and value point cloud image representing the grayscale and value of the reference part.

[0158] Specifically, the fourth point cloud row vectors of the plurality of image information are spliced ​​alternately 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, the top centroid position of the feature part is obtained according to the centroid position point cloud map and the grayscale sum value point cloud map, including: determining the position of the feature part according to 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 object to be tested 100 . The position of the feature part on the object to be tested 100 can be determined through the distribution of the centroid position in the centroid position point cloud map.

[0161] In this embodiment, in determining the position of the feature portion according to the centroid position point cloud map, the position of the feature portion is determined by combining the total grayscale sum value point cloud map and the centroid position point cloud map.

[0162] The characteristic part and the reference part have different reflected light intensities after being irradiated by the incident light, and there is a relatively obvious difference in the total grayscale and the value point cloud map. Therefore, combining the total grayscale and the value point cloud map as an aid to determining the position of the characteristic part is conducive to more accurate determination of the position of the characteristic part.

[0163] In this embodiment, points of the first set area at the position of the feature part are obtained in the centroid position point cloud map, and points of the second set area at the position of the feature part are obtained in the grayscale and value point cloud map, and the first set area and the second set area are the same size.

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

[0165] The first grayscale and value point cloud image corresponds to the first region of interest, that is, corresponds to 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 image and the first grayscale and value point cloud image 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 measurement point cloud data; the grayscale and value corresponding to the points in the second set area is used as the top measurement grayscale and value; based on the top measurement point cloud data and the top measurement grayscale and value, the top centroid position of the feature part is obtained.

[0167] That is, the top centroid position of the feature portion is obtained according to the centroid position and grayscale sum value in the same area.

[0168] In this embodiment, the point in the centroid position point cloud map is used as the first point, and the point in the first grayscale and value 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 measurement point cloud data and the top measurement grayscale and value, including: using the top measurement grayscale and value of each second point in the first set area of ​​the first grayscale and value point cloud map as the weight of the top measurement point cloud data of the first point at the corresponding position of the first set area of ​​the centroid position point cloud map, performing weighted averaging processing on the top measurement point cloud data, and obtaining the top centroid position.

[0170] The grayscale sum value can characterize the quality of the signal light of the obtained characteristic part. The larger the grayscale sum value is, the better the quality of the signal light characterizing the characteristic part is. In other words, the better the imaging quality of the characteristic part is, the larger the proportion it occupies in the weighted average processing, so that a more accurate height after weighted processing can be obtained.

[0171] Based on the weight, weighted averaging is performed on the top measurement point cloud data, which is beneficial to comprehensively consider the imaging quality of the feature parts at different relative positions, improve the accuracy of obtaining the top centroid position of the feature part, and thus help obtain high-precision detection results.

[0172] The top-measured grayscale and value are directly used as the weight corresponding to the top-measured point cloud data. While comprehensively considering the quality of the signal light at different relative positions, the weight is obtained more intuitively and the calculation method is simpler, which is conducive to the implementation of the detection method.

[0173] In other embodiments, the top centroid position of the feature part can also be obtained based on the top measurement point cloud data and the top measurement grayscale and value, including: dividing the top measurement point cloud data into multiple data columns along the scanning direction of the detection scan; using the top measurement grayscale and value of each second point in the first set area of ​​the first grayscale and value point cloud image as the weight of the top measurement point cloud data of the first point at the corresponding position of the first set area of ​​the centroid position point cloud image, performing weighted averaging processing on the top measurement 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 a feature portion with a relatively flat top, the average value of multiple top centroid sub-positions can be directly obtained as the top centroid position.

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

[0176] For feature parts with large surface unevenness, there is no exact position to characterize the height of the feature part. The fitting process is used to obtain the contour curve of the top centroid position, thereby obtaining the distribution of the top centroid position of the feature part surface. Subsequently, the height distribution of the feature part surface is obtained accordingly, and then according to actual needs, the height point that meets the needs is adopted from the height distribution.

[0177] In this embodiment, obtaining the bottom centroid position of the reference part according to the plurality of image information includes: determining the position of the reference part according to the second grayscale and value point cloud image.

[0178] The second grayscale and value point cloud map represents the grayscale and value corresponding to the reference portion, so that the position of the reference portion can be determined according to the second grayscale and value 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 measurement point cloud data; and the average value of the bottom measurement point cloud data is taken as the bottom centroid position.

[0180] Usually, the surface of the object to be measured 100 is relatively flat, and the grayscale and value correspondences of various reference parts are not very different, so the average value of the bottom measurement point cloud data can be directly taken as the bottom centroid position.

[0181] Execute step S4: obtain a measured height difference between the feature portion and the reference portion according to the first detection information and the second detection information.

[0182] In this embodiment, the measured height difference between the characteristic portion and the reference portion is obtained according to the first detection information and the second detection information, including: obtaining the measured height difference between the characteristic portion and the reference portion along the direction perpendicular to the surface of the object to be measured 100 according to the position difference between the top center of mass position and the bottom center of mass position.

[0183] The measured height of the feature part is obtained according to the position difference between the top center of mass position and the bottom center of mass position. The measured height difference between the feature part and the surface of the object to be measured 100 can be obtained, and the actual height of the feature part is obtained accordingly, which is beneficial to reduce the detection error caused by the unevenness of the object to be measured 100 itself, thereby facilitating more accurate acquisition of the measured height of the feature part.

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

[0185] By taking the product of the pixel value and the height value corresponding to the unit 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 a height value in three-dimensional measurement.

[0186] In this embodiment, after the detector collects signal light at each relative position to obtain image information corresponding to the incident light spot, and before obtaining the top centroid position of the characteristic part and the bottom centroid position of the reference part according to multiple image information, it also includes: denoising the image information separately.

[0187] De-noising the image information is beneficial to obtaining image information with higher accuracy and reducing the interference of image noise, which is beneficial to subsequently accurately obtaining height information corresponding to the feature part.

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

[0189] The median filter has a good filtering effect on salt and pepper noise (i.e., impulse noise), and while filtering the noise, it can protect the edge of the signal so that it is not blurred. In addition, the median filter algorithm is relatively simple and easy to implement with hardware.

[0190] In this embodiment, after the detector collects signal light at each relative position to obtain image information corresponding to the incident light spot, and before obtaining the top centroid position of the characteristic part and the bottom centroid position of the reference part based on multiple image information, it also includes: performing threshold segmentation processing on the image information, and setting the grayscale value of the point in the image information whose grayscale value is lower than the preset grayscale value to zero.

[0191] The sampling spots of the sampling points of each image information are different, so the benchmarks for threshold segmentation are different, so it is necessary to set a grayscale threshold for each image information. Grayscale threshold segmentation is helpful to more accurately filter out the sampling spots of stray light on the surface of the object to be tested 100, and reduce the interference of stray light on the imaging of the characteristic part.

[0192] Accordingly, this embodiment also provides a detection system. Figure 8 It 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 detected; an interest region acquisition module 502, used to acquire a first interest region and a second interest region of the detection image, the first interest region includes image information of the characteristic part, and the second interest region includes image information of the reference part; a detection information acquisition module 503, used to obtain first detection information of the characteristic part according to the first interest region, and obtain second detection information of the reference part according to the second interest region; a measured height difference acquisition module 504, used to obtain a measured height difference between the characteristic part and the reference part according to the first detection information and the second detection information.

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

[0195] Specifically, the characteristic portion is a bump to be measured, and the reference portion is a 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 detected.

[0197] The detection image is obtained to prepare for the subsequent acquisition of image information of the characteristic part and the reference part.

[0198] In this embodiment, optical detection is suitable for forming an incident light spot on the surface of the object to be tested having a sampling point through incident light, and collecting signal light from the sampling point through a detector to obtain the measured height of the characteristic part according to the signal light, and the sampling point includes the characteristic part and the reference part.

[0199] Specifically, in this embodiment, obtaining 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 through reflection from the surface of the object to be tested; and obtaining a 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 performing detection scanning on the object to be detected to obtain a plurality of detection images of the object to be detected.

[0201] In this embodiment, the optical detection is suitable for performing detection and scanning on the object to be detected by using an incident light spot.

[0202] Specifically, in this embodiment, incident light is reflected on the surface of the object to be measured to form signal light, forming a triangular optical path, so that the height of the characteristic part is detected by using the triangulation method.

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

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

[0205] The embodiment of the present invention further provides a device, which can implement the detection method provided by the embodiment of the present invention by loading the above detection method in the form of a program. An optional hardware structure of the terminal device provided by the embodiment of the present invention can be as follows Fig. 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 the communication bus 04. The communication interface 02 can be an interface of a communication module for network communication, such as an interface of a GSM module. The processor 01 may be a central processing unit CPU, or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement an embodiment of the present invention. The memory 03 may include a high-speed RAM memory, and may also include a non-volatile memory (NVM), such as at least one disk storage. Among them, the memory 03 stores one or more computer instructions, and the one or more computer instructions are executed by the processor 01 to implement the detection method provided in the embodiment of the present invention.

[0207] It should be noted that the above-mentioned terminal device may also include other devices (not shown) that may not be necessary for understanding the contents disclosed in the embodiments of the present invention; given that these other devices may not be necessary for understanding the contents disclosed in the embodiments of the present invention, the embodiments of the present invention will not introduce them one by one.

[0208] An embodiment of the present invention further provides a storage medium, wherein the storage medium stores one or more computer instructions, and the one or more computer instructions are used to implement the detection method provided by the embodiment of the present invention.

[0209] The embodiment of the present invention obtains the first region of interest and the second region of interest of the detection image to respectively obtain the first detection information of the characteristic part and the second detection information of the reference part, which is conducive to obtaining more accurate detection information, while saving computing power, improving detection efficiency, and realizing high-stability and high-precision optical detection.

[0210] The above-mentioned embodiments of the present invention are combinations of elements and features of the present invention. Unless otherwise mentioned, the elements or features may be considered as optional. Each element or feature may be put into practice without being combined with other elements or features. In addition, the 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 one embodiment may be included in another embodiment, and may be replaced by the corresponding construction of another embodiment. It is obvious to those skilled in the art that claims that do not have a clear reference relationship to each other in the attached claims may be combined into embodiments of the present invention, or may be included as new claims in the amendment after submitting this application.

[0211] Embodiments of the present invention may be implemented by various means such as hardware, firmware, software or a combination thereof. In a hardware configuration, the method according to an exemplary embodiment of the present invention may 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 may be implemented in the form of modules, processes, functions, etc. The software code may be stored in a memory unit and executed by a processor. The memory unit is located inside or outside the processor and may send data to the processor 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 implement or use the present invention. Various modifications to these embodiments will be 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 present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0213] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope defined by the claims.

Claims

1. An optical detection method, characterized in that: For detecting the height difference between the characteristic part and the reference part of the surface of the object to be measured, the detection method comprises: Acquiring a detection image of the object to be detected; 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 characteristic portion, and the second region of interest includes image information of the reference portion; Obtain first detection information of the characteristic portion according to the first region of interest, and obtain second detection information of the reference portion according to the second region of interest; A measured height difference between the feature portion and the reference portion is obtained based on the first detection information and the second detection information.

2. The optical detection method according to claim 1, characterized in that: Acquiring a first region of interest and a second region of interest of the detection image, comprising: acquiring a light parameter value distribution of the detection image, wherein the light parameter value distribution is a corresponding relationship between a position of each pixel point in the detection image and a light parameter value, wherein the light parameter value includes a grayscale value; A first region of interest and a second region of interest of the detection image are acquired according to the light parameter value distribution.

3. The optical detection method according to claim 2, characterized in that: 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 through reflection from the surface of the object to be tested, and acquiring a detection image corresponding to the incident light spot by collecting the signal light through a detector; Acquiring the light parameter value distribution of the detection image, comprising: performing one-dimensional projection on the image information of the detection image along a first direction to obtain first projection data, wherein the first projection data represents the corresponding relationship between the position of each pixel point in a second direction and the projection value, the projection value being the maximum value of the light parameter value, the first direction being the row direction of the detector target surface, and the second direction being the column direction of the detector target surface; Acquiring the first region of interest and the second region of interest according to the light parameter value distribution, comprising: determining the first region and the second region along the second direction according to the detection image, wherein the first region includes the image information of the characteristic portion, and the second region includes the image information of the reference portion; acquiring 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; acquiring the first region of interest according to the first peak position, wherein the boundaries of the first region of interest along the second direction are located on both sides of the first peak position; acquiring the second region of interest according to the second peak position, wherein the boundaries of the second region of interest along the second direction are located on both sides of the second peak position; or, Acquiring the light parameter value distribution of the detection image also includes: splicing the first projection data corresponding to the plurality of detection images along the first direction to obtain a data matrix; Performing a one-dimensional projection on the data matrix along the first direction to obtain second projection data, wherein the second projection data represents a corresponding relationship between positions of a plurality of pixel points in the second direction and projection values, wherein the projection value is a maximum value, a minimum value or a mean value of the light parameter value; Acquiring the first region of interest and the second region of interest according to the light parameter value distribution includes: acquiring 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; acquiring the first region of interest according to the first peak position, and the boundaries of the first region of interest along the second direction are located on both sides of the first peak position; acquiring the second region of interest according to the second peak position, and the boundaries of the second region of interest along the second direction are located on both sides of the second peak position.

4. The optical detection method according to claim 3, characterized in that: The optical detection method is suitable for performing detection scanning on the object to be detected to obtain multiple detection images of the object to be detected; The first direction is a scanning direction perpendicular to the detection scan, and the second direction is a scanning direction of the detection scan.

5. The optical detection method according to claim 4, characterized in that: Acquiring the first region of interest according to the first peak position, and acquiring the second region of interest according to the second peak position, comprises: acquiring, according to the first peak position, a first position region corresponding to a point that is continuous with the first peak position and whose projection value is not 0; According to the second peak position, acquiring a second position area corresponding to points that are continuous with the second peak position and whose projection values ​​are not 0; According to the first location area, obtaining a location range covering the first location area along the second direction as the first area of ​​interest; According to the second location area, a location range covering the second location area along the second direction is obtained as the second range of interest.

6. The optical detection method according to claim 1, characterized in that: Obtaining first detection information of the characteristic portion according to the first region of interest, and obtaining second detection information of the reference portion according to the second region of interest, including: obtaining a top centroid position of the characteristic portion according to the first region of interest, and obtaining a bottom centroid position of the reference portion according to the second region of interest; Obtaining the measured height difference between the feature part and the reference part according to the first detection information and the second detection information includes: obtaining the measured height difference between the feature part and the reference part along the direction perpendicular to the surface of the object to be measured according to the image position difference between the top centroid position and the bottom centroid position.

7. The optical detection method according to claim 6, characterized in that: The optical detection is suitable for performing detection scanning on the object to be detected by using an incident light spot to obtain a plurality of detection images of the object to be detected; Obtaining the top centroid position of the characteristic portion according to the first region of interest, and obtaining the bottom centroid position of the reference portion according to the second region of interest, comprising: using the incident light spot to perform a detection scan on the object to be detected, so that the incident light spot and the object to be detected are relatively translated, so as to obtain a detection image corresponding to the incident light spot through a detector; Acquire the top centroid position of the feature part according to the first regions of interest of the plurality of detection images; The bottom centroid position of the reference part is obtained according to the second regions of interest of the plurality of detection images.

8. The optical detection method according to claim 7, characterized in that: Obtaining the top centroid position of the feature portion according to the first regions of interest of the plurality of detection images, comprising: obtaining a centroid position point cloud map and a grayscale and value point cloud map of the object to be detected according to the first regions of interest and the second regions of interest of the plurality of detection images, wherein the centroid position point cloud map is a correspondence between different positions on the surface of the object to be detected and the centroid position, and the grayscale and value point cloud map is a correspondence between different positions on the surface of the object to be detected and the grayscale and value; The top centroid position of the feature portion is obtained according to the centroid position point cloud image and the grayscale and value point cloud image.

9. The optical detection method according to claim 8, characterized in that: Obtaining the top centroid position of the feature portion according to the centroid position point cloud map and the grayscale and value point cloud map, including: determining the position of the feature portion according to the centroid position point cloud map; Acquire points of a first set area at the position of the feature part in the centroid position point cloud map, and acquire points of a second set area at the position of the feature part in the grayscale and value point cloud map, wherein the first set area and the second set area have the same size; Using the centroid position point cloud data corresponding to the points in the first set area as top measurement point cloud data; Taking the grayscale sum value corresponding to the points in the second set area as the top measured grayscale sum value; The top centroid position of the feature portion is obtained according to the top measurement point cloud data and the top measurement grayscale and value.

10. The optical detection method according to claim 6, characterized in that: According to the image position difference between the top centroid position and the bottom centroid position, the measured height difference between the feature part and the reference part is obtained along a direction perpendicular to the surface of the object to be measured, including: obtaining the pixel value corresponding to the position difference between the top centroid position and the bottom centroid position; and taking the product of the pixel value and the actual height value corresponding to the unit pixel as the measured height difference between the feature part and the reference part.

11. An optical detection system, characterized in that: For detecting the height difference between the characteristic part and the reference part of the surface of the object to be measured, the detection system comprises: A detection image acquisition module, used to acquire a detection image of the object to be detected; An area of ​​interest acquisition module, used to acquire a first area of ​​interest and a second area of ​​interest of the detection image, wherein the first area of ​​interest includes image information of the characteristic portion, and the second area of ​​interest includes image information of the reference portion; a detection information acquisition module, configured to obtain first detection information of the characteristic portion according to the first region of interest, and obtain second detection information of the reference portion according to the second region of interest; A measured height difference acquisition module is used to obtain a measured height difference between the feature portion and the reference portion according to the first detection information and the second detection information.

12. A device, characterized in that: The method comprises at least one memory and at least one processor, wherein the memory stores one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the detection method according to any one of claims 1 to 10.

13. A storage medium, characterized in that: The storage medium stores one or more computer instructions, and the one or more computer instructions are used to implement the detection method according to any one of claims 1-10.

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