公开(公告)号：US20240160089A1

公开(公告)日：2024-05-16

申请号：US18570881

申请日：2022-03-10

Applicant: HAMAMATSU PHOTONICS K.K.

Inventor： Akari ITO ,  Tomochika TAKESHIMA

IPC: G03B13/36 ,  G02B7/28

CPC classification number: G03B13/36 ,  G02B7/28

Abstract: A focal position estimation system is a system for estimating a focal position when in focus corresponding to an estimation target image, and includes: an estimation target image acquisition unit that acquires an estimation target image; and a focal position estimation unit that outputs a feature quantity of the estimation target image from the estimation target image by using a feature quantity output model and estimates a focal position when in focus corresponding to the estimation target image from the output feature quantity, wherein the feature quantity output model is generated by machine learning from a plurality of learning images associated with focal position information related to a focal position at the time of imaging, and feature quantities of two different learning images are compared with each other according to focal position information associated with the two different learning images, and machine learning is performed based on the comparison result.

公开(公告)号：US20240402092A1

公开(公告)日：2024-12-05

申请号：US18698876

申请日：2022-06-22

Applicant: HAMAMATSU PHOTONICS K.K.

Inventor： Akira SHIMASE ,  Tomochika TAKESHIMA ,  Akari ITO

IPC: G01N21/88 ,  G01N21/95 ,  G01N21/956 ,  G02B7/36

Abstract: An autofocus support method according to an embodiment supports autofocus for a semiconductor device having a substrate and a device pattern formed on one main surface side of the substrate. The method includes: a step of acquiring a first image focused on the substrate; a step of acquiring a spatial frequency image from the first image by Fourier transform and generating mask data for masking linear patterns in the same direction on the substrate based on the spatial frequency image; a step of performing filtering on a plurality of second images, which are captured by using an imaging device while changing the focal position of the imaging device on the other main surface side of the substrate, by using the mask data; and a step of focusing the imaging device on the device pattern based on the second image after filtering.

公开(公告)号：US20240290080A1

公开(公告)日：2024-08-29

申请号：US18570937

申请日：2022-03-10

Applicant: HAMAMATSU PHOTONICS K.K.

Inventor： Akari ITO ,  Tomochika TAKESHIMA

IPC: G06V10/778 ,  G06V10/75

CPC classification number: G06V10/778 ,  G06V10/751

Abstract: A feature quantity output model generation system is a system for generating a feature quantity output model to which information based on an image is input and which outputs a feature quantity of the image, and includes: a learning image acquisition unit that acquires a plurality of learning images associated with focal position information related to a focal position at the time of imaging; and a feature quantity output model generation unit that generates a feature quantity output model by machine learning from the acquired learning images, wherein the feature quantity output model generation unit compares the feature quantities of two different learning images according to focal position information associated with the two different learning images and performs machine learning based on the comparison result.

公开(公告)号：US20240282000A1

公开(公告)日：2024-08-22

申请号：US18570913

申请日：2022-03-10

Applicant: HAMAMATSU PHOTONICS K.K.

Inventor： Akari ITO ,  Tomochika TAKESHIMA

IPC: G06T7/73 ,  G06T7/00

CPC classification number: G06T7/73 ,  G06T7/0004 ,  G06T7/0012 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148

Abstract: An inclination estimation system is a system for estimating the inclination of an imaging target captured in an image, and includes: an estimation target image acquisition unit for acquiring estimation target images from the image; a focal position estimation unit for outputting feature quantities from estimation target images by using a feature quantity output model and estimating focal positions when in focus corresponding to the estimation target images; and an inclination estimation unit for estimating the inclination of the imaging target from the focal positions when in focus, wherein the feature quantity output model is generated by machine learning from a learning images associated with focal position information, and feature quantities of two different learning images are compared with each other according to focal position information associated with the two different learning images, and machine learning is performed based on a result of the comparison.