Image acquisition control method and device, equipment, storage medium and product

Abstract

The invention discloses an image taking control method and device, equipment, a storage medium and a product, and relates to the technical field of wafer image taking, and the image taking control method comprises the steps: transferring a wafer to be subjected to image taking, of which the center alignment is completed at a wafer edge finder, to a defect detection platform through a wafer conveying fork; and in different target light fields, through different types of cameras in a preset visual range, preset coordinates are traversed on the defect detection platform, shooting is carried out in sequence, defect images are obtained, the target light fields comprise a bright field, a dark field and a PL field, and the defect images comprise surface defect features, scratch features and growth defect features. According to the method and the device, the wafer surface defects and the growth defects of the deep layer of the wafer can be shot, the scratch features can also be shot, relatively comprehensive defect features can be covered, and the image quality of the shot defect image is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wafer image taking, and particularly relates to a method and device for taking image control, equipment, storage medium and product. BACKGROUND

[0002] In the related art, a camera + a capture card + a lens + a light source are used to detect different defects of a wafer under different light fields, such as a light field and a PL field, and to take defect images. However, under the above light source, only the surface defects of the wafer and the growth defects of the deep layer of the wafer can be taken, which cannot cover the relatively comprehensive defect characteristics of the wafer, and reduces the image quality of the taken defect images. SUMMARY

[0003] The main purpose of the present application is to provide a method and device for taking image control, equipment, storage medium and product, which aims to solve the technical problem that the existing light field cannot cover the relatively comprehensive defect characteristics of the wafer, and reduces the image quality of the taken defect images.

[0004] To achieve the above-mentioned purpose, the present application provides a method for taking image control, which comprises the following steps: A wafer transfer fork is used to transfer a wafer to be taken to a defect detection platform, which has completed center alignment at a wafer edge finder. Different types of cameras with a preset visual range are used to take images in sequence under different target light fields on the defect detection platform at preset coordinates, and defect images are obtained, wherein the target light field includes a bright field, a dark field and a PL field, and the defect images include surface defect characteristics, scratch characteristics and growth defect characteristics.

[0005] In an embodiment, the step of taking images in sequence under different target light fields on the defect detection platform at preset coordinates by different types of cameras to obtain defect images comprises the following steps: When the target light field is the bright field, a line-scan camera is used to take images of the wafer to be taken in sequence on the defect detection platform along the preset coordinates to obtain a first defect image, wherein the first defect image contains surface defect characteristics; When the target light field is the dark field, a face array camera is used to take images of the wafer to be taken in sequence on the defect detection platform along the preset coordinates to obtain a second defect image, wherein the second defect image contains scratch characteristics; When the target light field is the PL field, the face array camera is used to take images of the wafer to be taken in sequence on the defect detection platform along the preset coordinates to obtain a third defect image, wherein the third defect image contains growth defect characteristics of the deep layer of the wafer.

[0006] In an embodiment, the step of obtaining defect images by preset vision range cameras of different types under different target light fields and sequentially capturing images under preset coordinates on the defect detection platform is followed by: using the preset coordinates corresponding to the defect images as the identification of the defect images; sending the defect images with the identification to a Flask server through a network cable to enable the Flask server to detect defects in the defect images and return the defect images with defect detection results to the local, wherein the defect detection results include defect type, defect location, and defect size; until the preset coordinates are completed, the defect images are spliced into wafer defect images based on the preset coordinates corresponding to the defect images.

[0007] In an embodiment, the step of transferring the wafer to be imaged, whose center alignment has been completed at the wafer edge finder, to the defect detection platform by the wafer transfer fork is preceded by: placing the wafer to be imaged at the wafer edge finder by the wafer fork and collecting pixel information of the wafer when it rotates on the wafer edge finder, wherein the wafer rotates on the chuck of the wafer edge finder by suction; determining the edge point coordinates of the wafer based on the pixel information; obtaining a fitting circle based on the edge point coordinates and using the center of the fitting circle as the center of the wafer; aligning the center of the wafer with the center of the wafer edge finder.

[0008] In an embodiment, the step of aligning the center of the wafer with the center of the wafer edge finder is followed by: judging whether the wafer to be imaged has a flat edge based on the edge point coordinates deviating from the fitting circle; if so, determining the flat edge center of the flat edge; rotating the flat edge to a preset position of the wafer edge finder based on the flat edge center.

[0009] In an embodiment, the step of transferring the wafer to be imaged, whose center alignment has been completed at the wafer edge finder, to the defect detection platform by the wafer transfer fork, wherein the center of the wafer transfer fork is aligned with the center of the wafer to be imaged, is preceded by: establishing a coordinate system with the center of the wafer to be imaged as the coordinate origin; obtaining the diameter of the wafer to be imaged; dividing the wafer to be imaged based on the diameter to obtain a detection area; Determine a preset coordinate of the to-be-detected region in the coordinate system.

[0010] In addition, to achieve the above object, the present application further provides a picture taking control device, which comprises: The transferring module is configured to transfer the to-be-taken picture wafer, which has completed center alignment at the wafer edge finder, to a defect detection platform by a wafer transfer fork. The shooting module is configured to sequentially shoot at preset coordinates on the defect detection platform under different target light fields by different types of cameras with preset visual ranges, to obtain defect images, wherein the target light fields include bright field, dark field and PL field, and the defect images include surface defect features, scratch features and growth defect features.

[0011] In addition, to achieve the above object, the present application further provides a picture taking control device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the picture taking control method as described above.

[0012] In addition, to achieve the above object, the present application further provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the picture taking control method as described above.

[0013] In addition, to achieve the above object, the present application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the picture taking control method as described above.

[0014] The one or more technical solutions provided by the present application have at least the following technical effects: In related technologies, a camera + acquisition card + lens + light source method is used to detect different defects on the wafer under different light fields, such as light field and PL field, and to capture defect images. However, under the above light source, only surface defects and deep growth defects of the wafer can be captured, so the captured defect images cannot cover all defects of the wafer, which reduces the image quality of the captured defect images. This application uses a wafer transfer fork to transfer a wafer to be imaged, which has been centered at the wafer edge finder, to a defect detection platform. Under different target light fields, different types of cameras with preset visual ranges sequentially capture images at preset coordinates on the defect detection platform to obtain defect images. The target light fields include bright field, dark field, and PL field. The defect images include surface defect features, scratch features, and growth defect features. After the wafer to be imaged is placed on the platform, this application sequentially captures images at preset coordinates in the target light fields, including the bright field, dark field, and PL field, to obtain defect images including surface defect features, scratch features, and growth defect features. By adding a dark field, this application can capture not only wafer surface defects and deep growth defects, but also scratch features, which can cover a more comprehensive range of defect features and improve the image quality of the captured defect images. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating an embodiment of the image acquisition control method of this application. Figure 2 This is a schematic diagram of defect image capture under a PL field in the image acquisition control method of this application; Figure 3 Schematic diagram of defect images captured by the image acquisition control method of this application under different light fields; Figure 4 This is a schematic diagram of the map diagram for the map acquisition control method of this application; Figure 5 This is a schematic diagram of the area division for the mapping control method of this application; Figure 6 This is a flowchart illustrating Embodiment 2 of the image acquisition control method of this application; Figure 7This is a schematic diagram of the module structure of the image-taking control device according to an embodiment of this application; Figure 8 This is a schematic diagram of the device structure of the hardware operating environment involved in the image capture control method in the embodiments of this application.

[0018] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0020] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0021] The main solution of this application embodiment is: to transfer the wafer to be picked up, which has been centered at the wafer edge finder, to the defect detection platform through a wafer transfer fork; under different target light fields, to take pictures sequentially through preset coordinates on the defect detection platform using different types of cameras with preset visual ranges to obtain defect images, wherein the target light field includes bright field, dark field and PL field, and the defect image includes surface defect features, scratch features and growth defect features.

[0022] In related technologies, a camera + acquisition card + lens + light source method is used to detect different defects on the wafer under different light fields, such as light field and PL field, and to capture defect images. However, under the above light source, only wafer surface defects and deep growth defects can be captured, resulting in defect images that cannot cover the more comprehensive defect features of the wafer, thus reducing the image quality of the captured defect images.

[0023] After the wafer to be imaged is placed on the platform, this application will take pictures sequentially by traversing preset coordinates in the target light field, including the light field, dark field and PL field, to obtain defect images including surface defect features, scratch features and growth defect features. By adding the dark field, this application will not only capture wafer surface defects and deep growth defects, but also scratch features, which can cover more comprehensive defect features and improve the image quality of the captured defect images.

[0024] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or image capture control device capable of performing the above functions. The following description uses an image capture control device as an example to illustrate this embodiment and the subsequent embodiments.

[0025] Based on this, the embodiments of this application provide an image acquisition control method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the image acquisition control method of this application.

[0026] In this embodiment, the image acquisition control method includes steps S10~S20: Step S10: Transfer the wafer to be picked up, which has been centered at the wafer edge finder, to the defect detection platform via the wafer transfer fork. It should be noted that the execution entity in this embodiment is an image acquisition control device. This image acquisition control device is equipped with a robotic arm, a defect detection platform, and a wafer edge finder. The wafer transfer fork is installed at the end of the robotic arm and is a fixture specifically used to carry and transfer wafers. The wafer edge finder is used to perform center correction and angle correction on the wafer. The defect detection platform scans with the wafer center as the coordinate origin.

[0027] Understandably, c uses an edge finder to align the wafer center and a crystal fork to precisely transfer the aligned wafer to the defect detection platform. This process ensures the accuracy and repeatability of subsequent high-resolution imaging and defect localization.

[0028] Step S20: Under different target light fields, different types of cameras with preset visual ranges are used to take pictures sequentially across preset coordinates on the defect detection platform to obtain defect images. The target light fields include bright field, dark field and PL field, and the defect images include surface defect features, scratch features and growth defect features.

[0029] It should be noted that the preset visual range is the smallest resolvable feature size of the system. Camera vision typically detects defects larger than 1.4µm, while conventional camera vision typically detects defects larger than 1.7µm. The detection of defects larger than 1.4µm can be achieved by adjusting the camera resolution. The image acquisition control device utilizes multi-light field coordination (bright field, dark field, and PL field) to cover three major categories of problems: surface contamination, mechanical damage, and material defects. Combined with a coordinate traversal mechanism, it achieves an automated, repeatable, and traceable defect imaging process for the entire film.

[0030] In one feasible implementation, step S10 may include the following steps: When the target light field is the bright field, the wafer to be imaged is sequentially photographed along a preset coordinate on the defect detection platform by a line scan camera to obtain a first defect image, wherein the first defect image contains surface defect features. Understandably, the light field source of the image acquisition control device illuminates the wafer surface at a vertical or near-vertical angle. Normal areas experience specular reflection, resulting in strong and concentrated signals. Defective areas (such as particles, pits, and protrusions) will cause changes in scattering or reflection direction, leading to localized abnormal brightness (brightening or darkening). The stage of the defect detection platform of the image acquisition control device moves at a constant speed along a preset coordinate path, and the line scan camera is triggered synchronously to collect specular reflection light line by line. All line data are stitched together to form a complete two-dimensional bright field image, i.e., the first defect image.

[0031] When the target light field is the dark field, the wafer to be imaged is captured sequentially along preset coordinates on the defect detection platform using an area array camera to obtain a second defect image, wherein the second defect image contains scratch features; It should be noted that the dark-field illumination light is incident at a large angle (not perpendicular) onto the wafer surface. Normally flat areas experience specular reflection, and the reflected light deviates from the camera's optical axis, resulting in a dark background. Defective areas (such as scratches, particles, and pits) induce anisotropic scattering, with some of the scattered light entering the camera lens, appearing as bright spots or bright streaks. The image capture control device activates the dark-field illumination, and the area scan camera performs a single-frame exposure of the current field of view, capturing the scattered light image to obtain the second defect image.

[0032] When the target light field is the PL field, the wafer to be imaged is captured sequentially along preset coordinates on the defect detection platform by the area array camera to obtain a third defect image, wherein the third defect image contains growth defect features deep within the wafer.

[0033] Understandably, photoluminescence (PL) fields use lasers of specific wavelengths (such as 325nm ultraviolet light, 405nm blue light, or 532nm green light) to irradiate the wafer surface. The photon energy excites electrons in the semiconductor material to transition from the valence band to the conduction band. When electron-hole pairs recombine, energy is released, emitting photoluminescence radiation with a longer wavelength. Defect regions alter the carrier recombination path, leading to a decrease in PL signal intensity, spectral shift, or abnormal spatial distribution. In other words, dark areas in the PL image represent defect areas, while bright areas represent high-quality crystals. Figure 2 , Figure 2 A schematic diagram of defect image capture under PL field is provided.

[0034] Furthermore, when the camera is at the new preset coordinates, the target light field will be activated sequentially, and defect images of different light fields at the same coordinates will be captured, ensuring that the image acquisition positions are strictly consistent, as referenced. Figure 3 , Figure 3 Schematic diagrams of defect images taken under different lighting conditions are provided.

[0035] In one possible implementation, the following steps may be included after step S20: The preset coordinates corresponding to the defect image are used as the identifier of the defect image; It should be noted that a defect image refers to a local image patch of multiple defects captured by the camera. The image name is used to identify the defect image. The image acquisition control device assigns preset coordinates to each captured defect image patch as its identifier, i.e., the image name, facilitating the reconstruction of the defect's location on the wafer after defect detection.

[0036] The defect image with the aforementioned identifier is sent to the Flask server via a network cable, so that the Flask server can perform defect detection on the defect image and return the defect image with the defect detection result marked on it to the local machine. The defect detection result includes the defect type, defect location, and defect size. Understandably, the Flask server uses the Flask framework to deploy deep learning models. The image capture control device also includes a host computer, which controls the camera to capture defect images and adds coordinate markers to the defect images. After the markers are added, the image is transmitted to the server via network cable for defect detection. The server takes about 500ms to complete the detection and returns the detection results to the host computer.

[0037] Furthermore, the Flask server performs instance segmentation on the defect image using the model, generates a pixel-level mask for each defect, accurately outlines its contour, and obtains the defect detection result.

[0038] Furthermore, the Flask server uses Tkinter (Python's standard GUI library) to develop a graphical user interface, with the following features: Set the input / output paths (image folder, result save location).

[0039] Select the model file path (model switching is supported).

[0040] Adjust key parameters: NMS threshold (IoU): controls the merging of overlapping boxes to avoid duplicate detection.

[0041] Confidence threshold: Filters out predictions with low confidence.

[0042] Whether to save the predicted image: for debugging and archiving purposes.

[0043] Furthermore, since the image capture speed is faster than the transmission and defect detection speed, this invention uses a multi-threaded transmission method between the host computer and the server for data interaction, thereby achieving real-time detection functionality.

[0044] Until the preset coordinates are traversed, the defect images are stitched together into a wafer defect image based on the preset coordinates corresponding to the defect images.

[0045] It should be noted that after the preset coordinate traversal is completed, meaning the entire inspection system has completely covered all areas of the wafer according to the predetermined scanning path, and has captured and processed the corresponding image at each location, the image acquisition control device also needs to stitch the detected defect information into a map based on the coordinate positions, using different colors to mark different types of defects (e.g., red = particles, blue = scratches, green = pits) to facilitate users in viewing the defect distribution and for reference. Figure 4 , Figure 4 A map diagram is provided.

[0046] Specifically, the steps for visualizing the Map are as follows: I. Data Collection and Preprocessing Data collection Defect data sets are acquired from wafer inspection equipment. This data is typically stored in file format, such as CSV (comma-separated values) files, Excel spreadsheets, or tables in a database. Data fields include defect type (e.g., scratches, holes, particles, etc.), size (expressed in micrometers or other suitable units), confidence level (usually a value between 0 and 1, indicating the reliability of the inspection algorithm in identifying the defect), and coordinates on the wafer (which can be polar coordinates, such as (r, θ), where r is the distance from the wafer center and θ is the angle; or rectangular coordinates, such as (x, y)).

[0047] Data cleaning Check the integrity of the data and remove records with too many missing values. For example, if a defect record lacks coordinate information, it may not be accurately displayed on the map, so it is necessary to consider deleting or supplementing the data.

[0048] Standardize the data format. If the units of dimensional data are inconsistent, they need to be converted to a unified unit, such as converting all data to micrometers. At the same time, standardize the naming of defect types to ensure that defects of the same type have consistent names in the data.

[0049] Data normalization (optional) For numerical data such as defect size and confidence level, if their ranges differ significantly, normalization can be performed. For example, normalizing both size and confidence level data to the range of 0-1 allows for better visual balance across different dimensions during subsequent visualization. The normalization formula can be: xnormalized = xmax - xmin, where x is the original data, and xmin and xmax are the minimum and maximum values ​​of the data column, respectively.

[0050] II. Visualization Dimension Definition First Visual Dimension - Defect Type Mapping Choose color as the primary dimension to map defect types. Assign a unique color to each defect type. For example, scratches are represented by red, holes by blue, and particles by green. Color selection can refer to common color coding standards or be determined based on user habits. When defining the color map, ensure sufficient contrast between colors to prevent users from having difficulty distinguishing different types of defects on the map.

[0051] Second visualization dimension - defect size or confidence mapping Choose the primitive size to map the defect size. Adjust the size of the primitives (such as circles, squares, etc., representing the defect) according to the defect size. For example, larger defects are represented by larger primitives, and smaller defects by smaller primitives. A linear or non-linear mapping function can be set, such as a linear mapping function: Primitive Size = a × Defect Size + b, where a and b are constants determined according to actual requirements.

[0052] Alternatively, you can choose to map the confidence level to transparency. Higher transparency indicates lower confidence. For example, when the confidence level is 1, the primitive is completely opaque; when the confidence level is 0, the primitive is completely transparent. Transparency mapping can also be achieved using a function, such as: transparency = 1 - confidence level.

[0053] III. Map Drawing and Rendering Create a display interface Create a display interface using a suitable graphics library (such as Matplotlib in Python, D3.js in JavaScript, etc.). This interface should be able to accommodate the entire shape of the wafer and scale according to the actual size of the wafer. Within the interface, set appropriate coordinate axes; if using polar coordinates, plot angle and radius scales; if using Cartesian coordinates, plot the x-axis and y-axis.

[0054] Defect data rendering Based on the coordinates of each defect, the corresponding primitive is placed on the Map. The color of each primitive is determined by the defect type, the size by the defect dimensions (if primitive size is chosen as the second dimension), or the transparency by the confidence level (if transparency is chosen as the second dimension).

[0055] During rendering, it's crucial to handle overlap between primitives. If multiple defects have similar coordinates, they may overlap. Strategies such as adjusting the transparency of primitives or adding gaps between overlapping primitives can be employed to ensure the user can clearly see each primitive.

[0056] Add interactive features (optional) To enhance user experience, interactive features can be added to the map. For example, when a user hovers their mouse over a feature, detailed information about the defect (including defect type, size, confidence level, and coordinates) can be displayed. Zoom functionality can also be added, allowing users to view defects in different areas of the map, as well as panning functionality for easier viewing of various parts of the map.

[0057] Furthermore, the communication between the host computer and the server can be improved through dual-channel asynchronous communication. Channel 1 is a high-priority metadata channel that does not transmit complete image data, but only the processed image data (defect type, coordinates, confidence level) and the image's unique coordinate identifier. This channel has a very small data volume and a very high transmission rate, used to refresh the map on the host computer in real time. Users can see the appearance of defects almost immediately, achieving "real-time perception." Channel 2 is an asynchronous image data channel used to transmit complete image data, employing a producer-consumer model and a ring buffer. The host computer acts as the producer, storing images in the buffer; the server acts as the consumer, reading images from the buffer sequentially for inspection. The transmission and processing of this channel are decoupled from Channel 1. It allows for some latency, but as long as the buffer is large enough, it ensures that all images are eventually processed without data loss.

[0058] In one feasible implementation, the following steps may be included before step S10: Establish a coordinate system with the center of the wafer to be imaged as the origin; It should be noted that the image acquisition control device usually selects the geometric center of the wafer as the origin (0,0) and defines the directions of the X and Y axes (usually along the diameter of the wafer) to establish the coordinate system.

[0059] Obtain the diameter of the wafer to be processed; Understandably, the image acquisition control device needs to obtain the exact diameter of the wafer to be inspected. Typically, the diameter of the wafer is given in inches (e.g., 6 inches, 8 inches, etc.).

[0060] Based on the diameter, the wafer to be imaged is divided to obtain the area to be detected; It should be noted that once the wafer diameter is known, the image acquisition control device can divide the wafer surface according to specific inspection requirements and standards to determine which areas need to be inspected, such as... Figure 4 As shown, Figure 5 A diagram showing the division of the region is provided. Figure 5 Each image in the image is 1024*1024 pixels, which corresponds to an actual size of 1.4336mm*1.4336mm.

[0061] Determine the preset coordinates of the region to be detected in the coordinate system.

[0062] Understandably, the image acquisition control device is based on Figure 5 The division results determine the row and column of each region, and use the row and column as the preset coordinates.

[0063] In this embodiment, not only wafer surface defects and deep wafer growth defects are captured, but also scratch features are captured, which can cover a more comprehensive range of defect features and improve the image quality of the captured defect images.

[0064] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 Before step S10, the image acquisition control method further includes steps S01 to S04: Step S01: Place the wafer to be retrieved into the wafer edge finder using a crystal fork, and collect pixel information of the wafer as it rotates in the wafer edge finder, wherein the wafer rotates by a suction cup adsorbed on the wafer edge finder. It should be noted that the robotic arm of the image acquisition control device places the wafer to be inspected onto the edge finder via a crystal fork. The vacuum chuck of the edge finder fixes and flattens the wafer, and the chuck drives the wafer to rotate smoothly for one revolution. During the rotation, sensors (such as linear CCD or cameras) continuously collect pixel information of the edge. Modern edge finders can achieve positioning accuracy of micrometers (μm) or even submicrometers. The scanning and processing process is usually completed within 4.9 seconds.

[0065] Step S02: Based on the pixel information, determine the coordinates of the edge points of the wafer; Understandably, pixel information is generated by the linear CCD continuously scanning the reflected light at a fixed radius as the wafer rotates, resulting in a two-dimensional data matrix. The image capture control device locates the position where the light intensity changes abruptly, i.e., the coordinates of the edge point (angle θ and corresponding radial position R).

[0066] Step S03: Based on the coordinates of the edge points, obtain the fitted circle, and take the center of the fitted circle as the center of the wafer; It should be noted that the mapping control device uses the least squares circle fitting algorithm to calculate the center coordinates and radius of the optimal fitted circle from these discrete points.

[0067] Specifically, the least squares circle fitting algorithm is based on the formula... The derivation is as follows, where (A, B) are the coordinates of the center of the circle. The derivation process is as follows: →

[0068] make , ,

[0069] The equation of the circular curve is obtained.

[0070] have to , ,

[0071] Furthermore, the image acquisition control device uses the measured coordinates of multiple edge points to solve equations and obtain the actual center coordinates of the circle. Through the classic mathematical method of least squares circle fitting, the ideal geometric center of the wafer is robustly and accurately estimated from the noisy actual measurement data.

[0072] Step S04: Align the center of the wafer with the center of the wafer edge finder.

[0073] Understandably, the image picking control device aligns the wafer center with the wafer edge finder center, so that the wafer fork can place the wafer in the same position on the defect detection platform each time. Furthermore, the image picking control device can also calculate the offset of the fitted circle center relative to the origin of the equipment coordinate system. When the robot arm (wafer fork) picks up the wafer next time, it will automatically move the offset in the opposite direction to ensure that the wafer center is aligned with the wafer fork center.

[0074] In one feasible implementation, the following steps are included after step S04: Based on the coordinates of the edge points that deviate from the fitted circle, it is determined whether the wafer to be imaged has a flat edge; It should be noted that, in the flat-edge region, the trajectory formed by the edge points deviates from the circle, forming a straight line segment with a longer chord length. That is, when fitting the circle, the points in the flat-edge region will deviate significantly from the fitted circle. Therefore, the image acquisition control device determines whether there is a significantly deviated straight line segment region by analyzing the radial deviation of all edge points relative to the fitted circle.

[0075] If it exists, then determine the center of the flat edge; Understandably, once the image acquisition control device confirms the existence of a flat edge, it can locate the center of the flat edge by analyzing the angular region with the largest deviation.

[0076] The flat edge is rotated to a preset position of the wafer edge finder based on the center of the flat edge.

[0077] It should be noted that the image acquisition control device controls the rotation mechanism to rotate the wafer so that the center of the flat edge is aligned with the preset reference position of the equipment (such as the 0° direction).

[0078] In this embodiment, through the collaboration of the optical system, image processing unit, and control unit, the edge of the wafer is precisely located, enabling high-speed and accurate completion of wafer center positioning and angle correction.

[0079] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the image capture control method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0080] This application also provides an image acquisition control device, please refer to... Figure 7 The image acquisition control device includes: The transfer module 10 is used to transfer the wafer to be picked up, which has been centered at the wafer edge finder, to the defect detection platform via the wafer transfer fork. The imaging module 20 is used to capture images sequentially across preset coordinates on the defect detection platform under different target light fields using different types of cameras with preset visual ranges, thereby obtaining defect images. The target light fields include bright fields, dark fields, and PL fields, and the defect images include surface defect features, scratch features, and growth defect features.

[0081] Optionally, the shooting module includes: The imaging submodule, when the target light field is a bright field, sequentially captures images of the wafer to be imaged along preset coordinates on the defect detection platform using a line scan camera to obtain a first defect image, wherein the first defect image contains surface defect features; when the target light field is a dark field, sequentially captures images of the wafer to be imaged along preset coordinates on the defect detection platform using an area scan camera to obtain a second defect image, wherein the second defect image contains scratch features; when the target light field is a PL field, sequentially captures images of the wafer to be imaged along preset coordinates on the defect detection platform using the area scan camera to obtain a third defect image, wherein the third defect image contains deep growth defect features of the wafer.

[0082] The detection submodule is used to use the preset coordinates corresponding to the defect image as the identifier of the defect image; send the defect image with the identifier to the Flask server via a network cable, so that the Flask server can perform defect detection on the defect image, and return the defect image with the defect detection result marked on it to the local machine, wherein the defect detection result includes defect type, defect location and defect size; until the preset coordinate traversal is completed, the defect images are stitched together into a wafer defect image based on the preset coordinates corresponding to the defect images.

[0083] Optionally, the transfer module includes: The alignment submodule is used to place the wafer to be retrieved onto the wafer edge finder via a crystal fork, and to collect pixel information of the wafer as the wafer edge finder rotates, wherein the wafer rotates by a suction cup adsorbed on the wafer edge finder; based on the pixel information, the coordinates of the edge points of the wafer are determined; based on the edge point coordinates, a fitted circle is obtained, and the center of the fitted circle is taken as the center of the wafer; the center of the wafer is aligned with the center of the wafer edge finder.

[0084] The segmentation submodule is used to establish a coordinate system with the center of the wafer to be imaged as the origin; obtain the diameter of the wafer to be imaged; segment the wafer to be imaged based on the diameter to obtain the detection area; and determine the preset coordinates of the detection area in the coordinate system.

[0085] Optionally, the alignment submodule includes: A rotation unit is used to determine whether the wafer to be taken has a flat edge based on the coordinates of the edge point that deviates from the fitted circle; if it does, the center of the flat edge is determined; and the flat edge is rotated to a preset position of the wafer edge finder based on the center of the flat edge.

[0086] The image acquisition control device provided in this application, employing the image acquisition control method in the above embodiments, can solve the technical problem of image acquisition control. Compared with the prior art, the beneficial effects of the image acquisition control device provided in this application are the same as those of the image acquisition control method provided in the above embodiments, and other technical features in the image acquisition control device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0087] This application provides an image capture control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the image capture control method in the above embodiment 1.

[0088] The following is for reference. Figure 8 The diagram illustrates a structural schematic of an image capture control device suitable for implementing embodiments of this application. The image capture control device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, tablets, digital broadcast receivers, PDAs (Personal Digital Assistants), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 8 The image capture control device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0089] like Figure 8As shown, the image capture control device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the image capture control device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the map acquisition control device to communicate wirelessly or wiredly with other devices to exchange data. Although map acquisition control devices with various systems are shown in the figures, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.

[0090] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0091] The image acquisition control device provided in this application, employing the image acquisition control method in the above embodiments, can solve the technical problem of image acquisition control. Compared with the prior art, the beneficial effects of the image acquisition control device provided in this application are the same as those of the image acquisition control method provided in the above embodiments, and other technical features in this image acquisition control device are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0092] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0093] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0094] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the image capture control method in the above embodiments.

[0095] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0096] The aforementioned computer-readable storage medium may be included in the drawing control device; or it may exist independently and not be assembled into the drawing control device.

[0097] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the image acquisition control device, the image acquisition control device: transfers the wafer to be acquired, which has been centered at the wafer edge finder, to the defect detection platform via a wafer transfer fork; and, under different target light fields, sequentially takes pictures of the defect detection platform at preset coordinates using different types of cameras with preset visual ranges to obtain defect images. The target light fields include bright field, dark field, and PL field, and the defect images include surface defect features, scratch features, and growth defect features.

[0098] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0100] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0101] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described image capture control method, thereby solving the technical problem of image capture control. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the image capture control method provided in the above embodiments, and will not be repeated here.

[0102] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the image capture control method described above.

[0103] The computer program product provided in this application can solve the technical problem of image acquisition control. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the image acquisition control method provided in the above embodiments, and will not be repeated here.

[0104] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.

Claims

1. An image acquisition control method, characterized in that, The image acquisition control method includes: The wafer to be picked up, which has been centered at the wafer edge finder, is transferred to the defect detection platform via the wafer transfer fork. Under different target light fields, different types of cameras with preset visual ranges are used to take pictures sequentially across preset coordinates on the defect detection platform to obtain defect images. The target light fields include bright field, dark field and PL field, and the defect images include surface defect features, scratch features and growth defect features.

2. The image acquisition control method as described in claim 1, characterized in that, The step of obtaining defect images by taking sequential images across preset coordinates on the defect detection platform under different target light fields using different types of cameras includes: When the target light field is the bright field, the wafer to be imaged is sequentially photographed along a preset coordinate on the defect detection platform by a line scan camera to obtain a first defect image, wherein the first defect image contains surface defect features. When the target light field is the dark field, the wafer to be imaged is captured sequentially along preset coordinates on the defect detection platform using an area array camera to obtain a second defect image, wherein the second defect image contains scratch features; When the target light field is the PL field, the wafer to be imaged is captured sequentially along preset coordinates on the defect detection platform by the area array camera to obtain a third defect image, wherein the third defect image contains growth defect features deep within the wafer.

3. The image acquisition control method as described in claim 1, characterized in that, The step of obtaining defect images by sequentially capturing images at preset coordinates using different types of cameras with preset visual ranges under different target light fields includes: The preset coordinates corresponding to the defect image are used as the identifier of the defect image; The defect image with the aforementioned identifier is sent to the Flask server via a network cable, so that the Flask server can perform defect detection on the defect image and return the defect image with the defect detection result marked on it to the local machine. The defect detection result includes the defect type, defect location, and defect size. Until the preset coordinates are traversed, the defect images are stitched together into a wafer defect image based on the preset coordinates corresponding to the defect images.

4. The image acquisition control method as described in claim 1, characterized in that, Prior to the step of transferring the wafer to be retrieved, which has been centered at the wafer edge finder, to the defect detection platform via the wafer transfer fork, the following steps are included: The wafer to be imaged is placed in the wafer edge finder using a crystal fork, and pixel information of the wafer is collected as the wafer edge finder rotates, wherein the wafer rotates by a suction cup adsorbed on the wafer edge finder; Based on the pixel information, the coordinates of the edge points of the wafer are determined; Based on the coordinates of the edge points, a fitted circle is obtained, and the center of the fitted circle is taken as the center of the wafer; Align the center of the wafer with the center of the wafer edge finder.

5. The image acquisition control method as described in claim 4, characterized in that, The step of aligning the wafer center with the wafer edge finder center is followed by: Based on the coordinates of the edge points that deviate from the fitted circle, it is determined whether the wafer to be imaged has a flat edge; If it exists, then determine the center of the flat edge; The flat edge is rotated to a preset position of the wafer edge finder based on the center of the flat edge.

6. The image acquisition control method as described in claim 1, characterized in that, Before the step of transferring the wafer to be retrieved, which has been centered at the wafer edge finder, to the defect detection platform via the wafer transfer fork, the following steps are also included: Establish a coordinate system with the center of the wafer to be imaged as the origin; Obtain the diameter of the wafer to be processed; Based on the diameter, the wafer to be imaged is divided to obtain the area to be detected; Determine the preset coordinates of the region to be detected in the coordinate system.

7. A picture acquisition control device, characterized in that, The device includes: The transfer module is used to transfer the wafer to be picked up, which has been centered at the wafer edge finder, to the defect detection platform via the wafer transfer fork. The imaging module is used to capture images of defects by taking pictures of different types of cameras with preset visual ranges at preset coordinates on the defect detection platform under different target light fields, thereby obtaining defect images. The target light fields include bright field, dark field and PL field, and the defect images include surface defect features, scratch features and growth defect features.

8. A map acquisition control device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the image capture control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the image acquisition control method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the image capture control method as described in any one of claims 1 to 6.

Images