PROCESSOR SYSTEM, SEMICONDUCTOR INSPECTION SYSTEM, AND PROGRAM

    公开(公告)号:US20230230886A1

    公开(公告)日:2023-07-20

    申请号:US18065698

    申请日:2022-12-14

    CPC classification number: H01L22/12 G06T7/50 G06T1/0007 G06T2207/30148

    Abstract: To provide a technique capable of quantitatively grasping a change in three-dimensional shape including a cross-sectional shape of a pattern within a surface of a wafer or between wafers in a non-destructive manner before cross-sectional observation. A processor system of a semiconductor inspection system acquires images captured by an electron microscope (SEM) for a sample (S102), calculates, for a reference region defined on a surface of the sample, first feature data corresponding to each of a plurality of locations in the reference region from the captured image (S103A), calculates a first statistical value based on the first feature data at the plurality of locations (S103B), calculates, for each of a plurality of evaluation regions defined as points or regions on the surface of the sample in correspondence with the reference region, second feature data corresponding to each of one or more locations in the evaluation region from the captured image, as feature data of the same type as the first feature data (S104A), and converts the second feature data using the first statistical value to obtain second feature data after conversion (S105).

    Pattern Matching Device, Pattern Measurement System, and Non-Transitory Computer-Readable Medium

    公开(公告)号:US20230071668A1

    公开(公告)日:2023-03-09

    申请号:US17800155

    申请日:2020-02-20

    Abstract: A pattern matching apparatus includes a computer system configured to execute pattern matching processing between first pattern data based on design data 104 and second pattern data representing a captured image 102 of an electron microscope. The computer system acquires a first edge candidate group including one or more first edge candidates, acquires a selection-required number (the number of second edge candidates to be selected based on the second pattern data), acquires a second edge candidate group including the second edge candidates of the selection-required number, acquires an association evaluation value for each of different association combinations between the first edge candidate group and the second edge candidate group, selects one of the combinations based on the association evaluation value, and calculates a matching shift amount based on the selected combination.

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