System and method for wafer inspection with a noise boundary threshold

    公开(公告)号:US10533953B2

    公开(公告)日:2020-01-14

    申请号:US15388577

    申请日:2016-12-22

    Abstract: A method includes receiving one or more images of three or more die of a wafer, determining a median intensity value of a set of pixel intensity values acquired from a same location on each of the three or more die, determining a difference intensity value for the set of pixel intensity values by comparing the median intensity value of the set of pixel intensity values to each pixel intensity value, grouping the pixel intensity values into an intensity bin based on the median intensity value of the set of pixel intensity values, generating an initial noise boundary based on a selected difference intensity value in the intensity bin, generating a final noise boundary by adjusting the initial noise boundary, generating a detection boundary by applying a threshold to the final noise boundary, and classifying one or more pixel intensity values outside the detection boundary as a defect.

    Method and System for Correlating Optical Images with Scanning Electron Microscopy Images

    公开(公告)号:US20190333206A1

    公开(公告)日:2019-10-31

    申请号:US16508778

    申请日:2019-07-11

    Abstract: The correlation of optical images with SEM images includes acquiring a full optical image of a sample by scanning the sample with an optical inspection sub-system, storing the full optical image, identifying a location of a feature-of-interest present in the full optical image with an additional sources, acquiring an SEM image of a portion of the sample that includes the feature at the identified location with a SEM tool, acquiring an optical image portion at the location identified by the additional source, the image portions including a reference structure, correlating the image portion and the SEM image based on the presence of the feature-of-interest and the reference structure in both the image portions and the SEM image, and transferring a location of the feature-of-interest in the SEM image into the coordinate system of the image portion of the full optical image to form a corrected optical image.

    Method and system for correlating optical images with scanning electron microscopy images

    公开(公告)号:US11244442B2

    公开(公告)日:2022-02-08

    申请号:US16508778

    申请日:2019-07-11

    Abstract: The correlation of optical images with SEM images includes acquiring a full optical image of a sample by scanning the sample with an optical inspection sub-system, storing the full optical image, identifying a location of a feature-of-interest present in the full optical image with an additional sources, acquiring an SEM image of a portion of the sample that includes the feature at the identified location with a SEM tool, acquiring an optical image portion at the location identified by the additional source, the image portions including a reference structure, correlating the image portion and the SEM image based on the presence of the feature-of-interest and the reference structure in both the image portions and the SEM image, and transferring a location of the feature-of-interest in the SEM image into the coordinate system of the image portion of the full optical image to form a corrected optical image.

    Adaptive care areas for die-die inspection

    公开(公告)号:US10997710B2

    公开(公告)日:2021-05-04

    申请号:US16158774

    申请日:2018-10-12

    Abstract: The present disclosure describes methods, systems, and articles of manufacture for performing a defect inspection of a die image using adaptive care areas (ACAs). The use of ACAs solve the problem of handling rotations of components that require rotating care areas; handling the situation where each care area requires its own rotation, translation, or affine transformation; and the situation of decoupling intensity differences caused by defects or process variation from intensity differences caused by size variations.

    Super-Resolution Defect Review Image Generation Through Generative Adversarial Networks

    公开(公告)号:US20200098101A1

    公开(公告)日:2020-03-26

    申请号:US16180957

    申请日:2018-11-05

    Abstract: A system for analyzing a sample includes an inspection sub-system and at least one controller. The inspection sub-system is configured to scan a sample to collect a first plurality of sample images having a first image resolution. The controller is configured to generate a defect list based on the first plurality of sample images. The controller is further configured to input images corresponding to the defect list into a neural network that is trained with source data including sample images having the first image resolution and sample images having a second image resolution higher than the first image resolution. The controller is further configured to generate a second plurality of sample images with the neural network based on the images corresponding to the defect list, where the second plurality of sample images have the second image resolution and correspond to the defect list.

    Segmentation for wafer inspection
    8.
    发明授权
    Segmentation for wafer inspection 有权
    晶圆检测分段

    公开(公告)号:US08831334B2

    公开(公告)日:2014-09-09

    申请号:US13742259

    申请日:2013-01-15

    Abstract: Methods and systems for segmenting pixels for wafer inspection are provided. One method includes determining a statistic for individual pixels based on a characteristic of the individual pixels in an image acquired for a wafer by an inspection system. The method also includes assigning the individual pixels to first segments based on the statistic. In addition, the method includes detecting one or more edges between the first segments in an image of the first segments and generating an edge map by projecting the one or more edges across an area corresponding to the image for the wafer. The method further includes assigning the individual pixels to second segments by applying the first segments and the edge map to the image for the wafer thereby segmenting the image. Defect detection is performed based on the second segments to which the individual pixels are assigned.

    Abstract translation: 提供了用于分割用于晶片检查的像素的方法和系统。 一种方法包括基于由检查系统为晶片获取的图像中的各个像素的特性来确定各个像素的统计量。 该方法还包括基于统计量将各个像素分配给第一段。 此外,该方法包括检测第一段的图像中的第一段之间的一个或多个边缘,并且通过将一个或多个边缘跨越与晶片的图像对应的区域来生成边缘图。 该方法还包括通过将第一段和边缘图应用于晶片的图像来将各个像素分配给第二段,从而分割图像。 基于分配了各个像素的第二段执行缺陷检测。

    Super-resolution defect review image generation through generative adversarial networks

    公开(公告)号:US10949964B2

    公开(公告)日:2021-03-16

    申请号:US16180957

    申请日:2018-11-05

    Abstract: A system for analyzing a sample includes an inspection sub-system and at least one controller. The inspection sub-system is configured to scan a sample to collect a first plurality of sample images having a first image resolution. The controller is configured to generate a defect list based on the first plurality of sample images. The controller is further configured to input images corresponding to the defect list into a neural network that is trained with source data including sample images having the first image resolution and sample images having a second image resolution higher than the first image resolution. The controller is further configured to generate a second plurality of sample images with the neural network based on the images corresponding to the defect list, where the second plurality of sample images have the second image resolution and correspond to the defect list.

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