Sensor-integrated Machine Vision System for Enhanced Defect Detection in Industrial Applications

With rapid advancements in high-tech industries, the demand for precision and efficiency in manufacturing has increased significantly.Automated optical inspection (AOI) systems have become essential across various sectors, expanding from electronics to food and pharmaceuticals, as quality control standards and consumer expectations rise.We present a machine vision approach for defect detection in paper cups, specifically targeting quality issues caused by stains or blemishes.Traditional binary detection methods, such as blob analysis, often struggle with light stain detection.Here, we implement an optical inspection method using blemish edge detection, which more accurately identifies subtle defects along the inner edges of paper cups.By enhancing defect detection accuracy, this method is aimed at improving product quality and optimizing production yield, making it a practical solution for large-scale, high-speed inspection requirements in modern manufacturing.

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Publication Details

Journal
Sensors and Materials
Published
2025-12-18
DOI
https://doi.org/10.18494/sam5700
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Sensor-integrated Machine Vision System for Enhanced Defect Detection in Industrial Applications

Kangzheng Chen, Yao‐Chin Wang, Shih-Hung Lin, Hsin‐Chin Chen et al.
Sensors and Materials
Industrial Vision Systems and Defect Detection
article

Sensor-integrated Machine Vision System for Enhanced Defect Detection in Industrial Applications

Kangzheng Chen, Yao‐Chin Wang, Shih-Hung Lin, Hsin‐Chin Chen, Ben-Yi Liau, Peter Yang
article en

Abstract

With rapid advancements in high-tech industries, the demand for precision and efficiency in manufacturing has increased significantly.Automated optical inspection (AOI) systems have become essential across various sectors, expanding from electronics to food and pharmaceuticals, as quality control standards and consumer expectations rise.We present a machine vision approach for defect detection in paper cups, specifically targeting quality issues caused by stains or blemishes.Traditional binary detection methods, such as blob analysis, often struggle with light stain detection.Here, we implement an optical inspection method using blemish edge detection, which more accurately identifies subtle defects along the inner edges of paper cups.By enhancing defect detection accuracy, this method is aimed at improving product quality and optimizing production yield, making it a practical solution for large-scale, high-speed inspection requirements in modern manufacturing.

Sensors and MaterialsVol. 37(12)
Cheng Shiu University
Openalex Percentile: Top 47%
Industrial Vision Systems and Defect Detection
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