Ghosting detection method, computer equipment and computer readable storage medium
By acquiring the projected image of the optical waveguide and analyzing the position information of the main image and ghost image, the problems of large errors and low efficiency of ghost detection of existing optical waveguides are solved, and more efficient and accurate detection is achieved.
CN119722553APending Publication Date: 2025-03-28ZHUHAI MOJIE TECH CO LTD
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Patent Information
- Application Number
- CN202311259283.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-09-27
- Publication Date
- 2025-03-28
AI Technical Summary
Technical Problem
The existing optical waveguide ghost detection methods have problems of large errors and low efficiency, and mainly rely on manual detection.
Method used
By obtaining the projected image formed by the emitted light of the light waveguide to be measured, the position information of the main image and ghosting image is determined, and the degree of ghosting is calculated, and the image analysis method is used to achieve automatic detection.
Benefits of technology
The accuracy and efficiency of ghost detection are improved, and compared with manual detection, the error is smaller and the detection speed is faster.
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Smart Images
Figure CN119722553A_ABST
Abstract
The invention discloses a ghosting detection method, computer equipment and a computer readable storage medium. The ghosting detection method comprises the following steps: acquiring a projection image formed by emergent light of a to-be-detected optical waveguide; determining a main image and a ghosting image for ghosting detection in the projection image; calculating first position information of the main image and second position information of the double image; and determining the ghosting degree of the main image and the ghosting image according to the first position information and the second position information. According to the method, ghosting detection is carried out through image analysis, and compared with a manual detection method, the detection error is smaller, and the detection efficiency is higher.
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