Vacuum cup surface defect detection method based on image features

By using a multi-angle image acquisition and feature extraction model, the problem of missing surface defects of thermos cups under single-angle detection was solved, achieving efficient and accurate detection of complex surfaces and improving defect identification capabilities and the stability of the detection system.

CN121660980APending Publication Date: 2026-03-13POLYBELL(GUANGZHOU) LTD
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Patent Information

Application Number
CN202511714373.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-21
Publication Date
2026-03-13

AI Technical Summary

Technical Problem

Existing methods for detecting surface defects in thermos cups rely on single-angle images, which makes it easy to miss local defects due to reflections or angle obscuring. This is especially true when the metallic luster is strong and the surface contour is complex, making it difficult to effectively capture directional and local defect features.

Method used

Multi-angle image acquisition is employed, and an angle feature extraction model is used to extract texture structure features, shape structure features, and reflection area features respectively. Texture disturbance index, contour offset index, and reflection focusing index are analyzed, and matching analysis is performed in combination with a preset defect judgment interval set.

Benefits of technology

It significantly improves the defect detection rate, can more clearly distinguish defect types, and has automated, auditable, and quantitative comparison capabilities, making it suitable for the inspection of thermos cups with complex surfaces.

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Abstract

The invention discloses a vacuum cup surface defect detection method based on image features, and relates to the technical field of image processing and intelligent detection. According to the vacuum cup surface defect detection method based on the image features, multi-angle image acquisition and preprocessing are performed, structural features such as texture, shape and reflection of the surface of a vacuum cup are extracted, a texture disturbance index, a contour offset index and a reflection focusing index are constructed, and the indexes are compared with a preset defect judgment interval, so that defect identification of images at various angles is realized; by constructing a multi-angle image feature extraction and index analysis mechanism, feature information such as texture, contour and reflection of the surface of the vacuum cup is accurately extracted, various abnormal degrees are quantified, automatic identification and marking are realized in combination with the preset defect judgment interval, the detection coverage range and the judgment accuracy can be effectively improved, and the detection efficiency is improved. The method enhances the recognition capability of complex defects, and is suitable for appearance quality inspection scenes with high requirements.
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