System and method for identifying surface crack in a glazing

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AI technical title is built by Patsnap AI team. It summarizes the technical point description of the patent document.
The system uses a mobile digital device and remote server to accurately detect and classify surface cracks in glazing materials, addressing the limitations of manual inspection methods.

WO2025069105A1 Publication Date: 2025-04-03SAINT GOBAIN SEKURIT FRANCE +1

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Patent Information

Application Number: PCT/IN2024/051905
Authority / Receiving Office: WO · WO
Patent Type: Applications
Current Assignee / Owner
Priority Date: 2023-09-29
Filing Date: 2024-09-29
Publication Date: 2025-04-03

Application Information

Patent Timeline

29 Sep 2023

Priority

29 Sep 2024

Application

PCT/IN2024/051905

03 Apr 2025

Publication

WO2025069105A1

IPC: G06T7/00; G01N21/88; G01B11/16

CPC: G01N2021/9586; G01N21/958; G06T7/0004; G06T2207/20081

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AI Technical Summary

Technical Problem

Current methods for detecting surface cracks in glazing materials rely on manual inspection, which is prone to human error and lacks reliability.

Method used

A system comprising a mobile digital device with an image capturing module and sensors, coupled with a remote server that processes images to identify and classify cracks as either surface or internal cracks.

Benefits of technology

The system provides a more accurate, efficient, and cost-effective solution for detecting surface cracks in glazing materials, reducing human error and enhancing reliability.

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Abstract

A system (100) for identifying surface crack in a glazing (102) is disclosed. The system 5 (100) comprises a mobile digital device (104) and a remote server (106). The mobile digital device (104) comprises an image capturing module configured to capture at least an image of the glazing, at least one sensor (206) configured to measure at least one position parameter associated with the mobile digital device (104). The remote server (106) comprises a database (304) and a processor (302). The processor (302) is 10 configured to receive the image of the glazing captured by the mobile digital device (104). Further, process the received image of the glazing to identify the presence of a crack, and determine whether the identified crack is a surface crack or an internal crack.

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