Invention Grant
- Patent Title: Methods and systems for crack detection using a fully convolutional network
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Application No.: US17602536Application Date: 2020-04-09
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Publication No.: US12039441B2Publication Date: 2024-07-16
- Inventor: Fu-Chen Chen , Mohammad R. Jahanshahi
- Applicant: Purdue Research Foundation
- Applicant Address: US IN West Lafayette
- Assignee: Purdue Research Foundation
- Current Assignee: Purdue Research Foundation
- Current Assignee Address: US IN West Lafayette
- Agency: Hartman Global IP Law
- Agent Gary M. Hartman; Domenica N. S. Hartman
- International Application: PCT/US2020/027488 2020.04.09
- International Announcement: WO2020/210506A 2020.10.15
- Date entered country: 2021-10-08
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/08 ; G06T7/00 ; G06T7/38 ; G06V10/80 ; G06V10/82

Abstract:
Systems and methods for detecting cracks in a surface by analyzing a video, including an full-HD video, of the surface. The video contains successive frames, wherein individual frames of overlapping consecutive pairs of the successive frames have overlapping areas and a crack that appears in a first individual frame of a consecutive pair of the successive frames also appears in at least a second individual frame of the consecutive pair. A fully convolutional network (FCN) architecture implemented on a processing device is then used to analyze at least some of the individual frames of the video to generate crack score maps for the individual frames, and a parametric data fusion scheme implemented on a processing device is used to fuse crack scores of the crack score maps of the individual frames to identify cracks in the individual frames.
Public/Granted literature
- US20220172346A1 METHODS AND SYSTEMS FOR CRACK DETECTION USING A FULLY CONVOLUTIONAL NETWORK Public/Granted day:2022-06-02
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