Surface anomaly detecting device, system, method, and non-transitory computer-readable medium

Patent metadata

Field	Value
Publication number	US-2022276181-A1
Application number	US-201917635523-A
Country	US
Kind code	A1
Filing date	Aug 26, 2019
Priority date	Aug 26, 2019
Publication date	Sep 1, 2022
Grant date	—

Abstract

The present disclosure is directed to providing a surface anomaly detecting device, a system, a method, and a non-transitory computer-readable medium that can identify an anomalous portion on a surface of a complex structure. A surface anomaly detecting device according to the present disclosure includes: dividing means configured to divide a structure into a plurality of clusters based on position information of a plurality of points on a surface of the structure; coupling means configured to create a cluster group by coupling together two or more of the clusters; determining means configured to determine a reflection luminance normal value of the cluster group based on a distribution of reflection luminance values at a plurality of points on a surface of the cluster group; and identifying means configured to identify an anomalous portion on the surface of the cluster group.

First claim

What is claimed is:

1 . A surface anomaly detecting device comprising:
at least one memory storing instructions, and at least one processor configured to execute the instructions to; divide a structure into a plurality of clusters based on position information of a plurality of points on a surface of the structure; create a cluster group by coupling together two or more of the clusters; determine a reflection luminance normal value of the cluster group based on a distribution of reflection luminance values at a plurality of points on a surface of the cluster group; and identify an anomalous portion on the surface of the cluster group based on a difference between the reflection luminance normal value and the reflection luminance value at each of the plurality of points on the surface of the cluster group.

2 . The surface anomaly detecting device according to claim 1 , wherein the at least one processor is configured to identify, among the plurality of points on the surface of the cluster group, a predetermined point where the difference between the reflection luminance value and the reflection luminance normal value exceeds a threshold as the anomalous portion.

3 . The surface anomaly detecting device according to claim 1 , wherein the at least one processor is configured to couple the clusters if the cluster group is included in a constituent element of the structure.

4 . The surface anomaly detecting device according to claim 1 , wherein the at least one processor is configured to create the cluster group by coupling a small cluster having no more than a predetermined number of points on a surface thereof and an adjacent cluster adjacent to the small cluster.

5 . The surface anomaly detecting device according to claim 1 , wherein the at least one processor is configured to determine, of the distribution of the reflection luminance values of the cluster group, the reflection luminance value with a highest frequency as the reflection luminance normal value.

6 . The surface anomaly detecting device according to claim 1 , wherein the at least one processor is configured to
identify, of the distribution of the reflection luminance values of the cluster group, a minimum dispersion cluster with a smallest dispersion, and determine, of the distribution of the reflection luminance values of the minimum dispersion cluster, the reflection luminance value with a highest frequency as the reflection luminance normal value.

7 . The surface anomaly detecting device according to claim 1 , wherein
an angle of laser incidence at a range-finding point that is one of the plurality of points on the surface of the cluster group is calculated based on a direction connecting the range-finding point of the cluster group with the surface anomaly detecting device and a direction of a normal at the range-finding point of the cluster group, and the reflection luminance value at the range-finding point of the cluster group is corrected based on the angle of laser incidence.

8 . The surface anomaly detecting device according to claim 1 , wherein
an angle of laser incidence at a range-finding point that is one of the plurality of points on the surface of the cluster group is calculated based on a direction connecting the range-finding point of the cluster group with the surface anomaly detecting device and a direction of a normal at the range-finding point of the cluster group, the at least one processor is configured to further divide the cluster group into subcluster groups based on the angle of laser incidence, the at least one processor is configured to determine a reflection luminance normal value of the subcluster group based on a distribution of reflection luminance values at a plurality of points on a surface of the subcluster group, and the at least one processor is configured to identify an anomalous portion on the surface of the subcluster group based on a difference between the reflection luminance normal value of the subcluster group and the reflection luminance value at each of the plurality of points on the surface of the subcluster group.

9 . The surface anomaly detecting device according to claim 7 , further comprising:
the at least one processor configured to calculate a plurality of complementary points that fill a space between a first cluster that is one of the clusters in the cluster group and a second cluster closest to the first cluster and create a complementary cluster having the plurality of complementary points on a surface thereof, wherein the at least one processor is configured to create a complementary cluster group by coupling the cluster group with the complementary cluster, a direction of a normal at the complementary point is estimated based on directions of normal at a plurality of the range-finding points surrounding the complementary point, and the anomalous portion of the structure is identified by use of the complementary cluster group instead of the cluster group.

10 . The surface anomaly detecting device according to claim 9 , wherein
a direction of a normal at a first range-finding point on one end portion of the first cluster facing the second cluster extends in the same direction as a direction of a normal at the complementary point closest to the first range-finding point, and a direction of a normal at a second range-finding point on one end portion of the second cluster facing the first cluster extends in the same direction as a direction of a normal at the complementary point closest to the second range-finding point.

11 . The surface anomaly detecting device according to claim 9 , wherein the direction of the normal at the complementary point is estimated by averaging directions of normal at a plurality of the range-finding points surrounding the complementary point.

12 . A system comprising:
a measuring device configured to acquire the reflection luminance values at a plurality of points on a surface of the cluster group; and the surface anomaly detecting device according to claim 1 , wherein the surface anomaly detecting device is configured to identify the anomalous portion on the surface of the cluster group.

13 . A method comprising:
dividing a structure into a plurality of clusters based on position information of a plurality of points on a surface of the structure; creating a cluster group by coupling together two or more of the clusters; determining a reflection luminance normal value of the cluster group based on a distribution of reflection luminance values at a plurality of points on a surface of the cluster group; and identifying an anomalous portion on the surface of the cluster group based on a difference between the reflection luminance normal value and the reflection luminance value at each of the plurality of points on the surface of the cluster group.

14 . A program that causes a computer to execute:
dividing a structure into a plurality of clusters based on position information of a plurality of points on a surface of the structure; creating a cluster group by coupling together two or more of the clusters; determining a reflection luminance normal value of the cluster group based on a distribution of reflection luminance values at a plurality of points on a surface of the cluster group; and identifying an anomalous portion on the surface of the cluster group based on a difference between the reflection luminance normal value and the reflection luminance value at each of the plurality of points on the surface of the cluster group.

Assignees

• Nec Corp

Inventors

• Ono Yoshimasa
• Tsuji Akira
• Abe Junichi

Classifications

• G01S17/89 Primary

  for mapping or imaging · CPC title

• G01N21/956

  Inspecting patterns on the surface of objects {(contactless testing of electronic circuits G01R31/308; testing currency G07D; manufacturing processes per se of semiconductor devices implementing a measuring step H10P74/20)} · CPC title

• G01N21/9515 Primary

  Objects of complex shape, e.g. examined with use of a surface follower device (measuring contours and curvatures G01B11/24) · CPC title

• G01N21/8851

  Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges (G01N21/8806 and G01N21/93 - G01N21/95692 take precedence; optical measurement of dimensions G01B11/00; optical scanning G02B26/10; image transformation G06T3/00; computerised image enhancement G06T5/00; image processing per se for flaw detection G06T7/0002) · CPC title

• G06T7/10

  Segmentation; Edge detection (motion-based segmentation G06T7/215) · CPC title