The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 26, 2019

Filed:

Aug. 16, 2017
Applicant:

Siemens Energy, Inc., Orlando, FL (US);

Inventors:

Ziyan Wu, Plainsboro, NJ (US);

Rameswar Panda, Riverside, CA (US);

Jan Ernst, Plainsboro, NJ (US);

Kevin P. Bailey, Chuluota, FL (US);

Assignee:

SIEMENS ENERGY, INC., Orlando, FL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/46 (2006.01); G06T 7/00 (2017.01); G01N 21/956 (2006.01); G06T 7/33 (2017.01);
U.S. Cl.
CPC ...
G01N 21/956 (2013.01); G06K 9/4661 (2013.01); G06T 7/001 (2013.01); G06T 7/0006 (2013.01); G06T 7/33 (2017.01);
Abstract

Method and system for detecting defects on surface of object are presented. An imaging device captures images of surface of object under ambient and dark field illumination conditions. The images are processed with a plurality of image operations to detect area of potential defect at location on surface of object based on predictable pattern consisting of bright and shadow regions. Kernels are defined corresponding to configurations of dark field illumination sources to enhance detecting potential defect. Areas of potential defect are cut from processed images to sub images. Sub images are stitched together to generate hypothesis of potential defect at location on surface of object. The hypothesis is classified with a classifier to determine whether the potential defect is true defect. The classifier is trained with training data having characteristics of true defect. The method provides efficient automated detection of micro defects on surface of object.


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