Defect detection on transparent or translucent wafers

    公开(公告)号:US10402963B2

    公开(公告)日:2019-09-03

    申请号:US15803091

    申请日:2017-11-03

    Abstract: Defect detection on transparent or translucent wafers can be performed on a die using references from the same die. A first calculated value based on a kernel size, such as a moving mean, is determined. A first difference is determined by subtracting the first calculated value from a pixel intensity. Candidate pixels with a first difference above a threshold are classified. A second calculated value based on a kernel size, such as a local median, is determined. A second difference is determined by subtracting the second calculated value from the pixel intensity. Pixels that include a defect are classified when the second difference is above the threshold.

    ADAPTIVE CARE AREAS FOR DIE-DIE INSPECTION
    12.
    发明申请

    公开(公告)号:US20190114758A1

    公开(公告)日:2019-04-18

    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.

    System, method and computer program product for identifying fabricated component defects using a local adaptive threshold

    公开(公告)号:US10043265B2

    公开(公告)日:2018-08-07

    申请号:US15221542

    申请日:2016-07-27

    Abstract: A system, method, and computer program product are provided for identifying fabricated component defects using a local adaptive threshold. In use, images are received for target and reference components of a fabricated device. Additionally, a difference image is generated from the target and reference component images, and defect candidates for the target component are identified from the difference image. Further, for each of the identified defect candidates at a location in the difference image: a threshold is determined based on a local area surrounding the location of the defect candidate, and a signal at the location of the defect candidate is compared to the threshold to determine whether the defect candidate is a defect.

    Context-Based Inspection for Dark Field Inspection
    15.
    发明申请
    Context-Based Inspection for Dark Field Inspection 有权
    基于情境的暗场检查

    公开(公告)号:US20150178907A1

    公开(公告)日:2015-06-25

    申请号:US14563845

    申请日:2014-12-08

    CPC classification number: G06T7/001 G06T7/33 G06T2207/30148

    Abstract: Methods and systems for detecting defects on a wafer are provided. One method includes altering one or more design clips based on how the one or more design clips will appear in output generated by a wafer inspection process for a wafer. The method also includes aligning the one or more altered design clips to the output generated for the wafer during the wafer inspection process. In addition, the method includes detecting defects on the wafer based on the output aligned to the one or more altered design clips.

    Abstract translation: 提供了用于检测晶片上的缺陷的方法和系统。 一种方法包括基于如何将一个或多个设计剪辑出现在由晶片的晶片检查过程产生的输出中来改变一个或多个设计剪辑。 该方法还包括在晶片检查过程中将一个或多个改变的设计剪辑与晶片产生的输出对准。 此外,该方法包括基于与一个或多个改变的设计剪辑对准的输出来检测晶片上的缺陷。

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

    公开(公告)号:US10410338B2

    公开(公告)日:2019-09-10

    申请号:US14506407

    申请日:2014-10-03

    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 for defocus detection
    17.
    发明授权

    公开(公告)号:US10372113B2

    公开(公告)日:2019-08-06

    申请号:US15669030

    申请日:2017-08-04

    Abstract: Two or more color data can be combined to form a new data source to enhance sensitivity to defocus signal. Defocus detection can be performed on the newly formed data source. In a setup step, a training wafer can be used to select the best color combination, and obtain defocus detection threshold. This can include applying a segment mask, calculating mean intensities of the segment, determining a color combination that optimizes defocus sensitivity, and generating a second segment mask based on pixels that are above a threshold to sensitivity. In a detection step, the selected color combination is calculated, and the threshold is applied to obtain defocus detection result.

    System and Method for Wafer Inspection with a Noise Boundary Threshold

    公开(公告)号:US20170284944A1

    公开(公告)日:2017-10-05

    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.

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