A hybrid defect detection method for compact camera lens

Production technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is insufficient for conducting quality control under this increased capacity. Therefore, high-speed and high-accuracy automated optical inspection is becoming increasingly...

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Main Authors: Chia-Feng Chang, Jiunn-Lin Wu, Kuan-Jen Chen, Ming-Chou Hsu
Format: Article
Language:English
Published: SAGE Publishing 2017-08-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814017722949
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author Chia-Feng Chang
Jiunn-Lin Wu
Kuan-Jen Chen
Ming-Chou Hsu
author_facet Chia-Feng Chang
Jiunn-Lin Wu
Kuan-Jen Chen
Ming-Chou Hsu
author_sort Chia-Feng Chang
collection DOAJ
description Production technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is insufficient for conducting quality control under this increased capacity. Therefore, high-speed and high-accuracy automated optical inspection is becoming increasingly crucial. In this article, we propose an automated inspection method for a compact camera lens using a circle Hough transformation, weighted Sobel filter, and polar transformation. Our analysis of defects in the compact camera lens identified problems including of the circular texture and the non-fixed position of the inspection region. To overcome these problems, we design an inspection algorithm for locating and inspecting a circular region. A machine learning support vector machine method is then applied for obtaining a precise detection result. The experimental results show that the proposed inspection method is suitable for detecting defects in a complicated circular inspection region, and that the proposed system exhibited high performance.
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spelling doaj.art-6eb656e893ec45a49cabb553b4196f3c2022-12-21T20:36:48ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402017-08-01910.1177/1687814017722949A hybrid defect detection method for compact camera lensChia-Feng ChangJiunn-Lin WuKuan-Jen ChenMing-Chou HsuProduction technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is insufficient for conducting quality control under this increased capacity. Therefore, high-speed and high-accuracy automated optical inspection is becoming increasingly crucial. In this article, we propose an automated inspection method for a compact camera lens using a circle Hough transformation, weighted Sobel filter, and polar transformation. Our analysis of defects in the compact camera lens identified problems including of the circular texture and the non-fixed position of the inspection region. To overcome these problems, we design an inspection algorithm for locating and inspecting a circular region. A machine learning support vector machine method is then applied for obtaining a precise detection result. The experimental results show that the proposed inspection method is suitable for detecting defects in a complicated circular inspection region, and that the proposed system exhibited high performance.https://doi.org/10.1177/1687814017722949
spellingShingle Chia-Feng Chang
Jiunn-Lin Wu
Kuan-Jen Chen
Ming-Chou Hsu
A hybrid defect detection method for compact camera lens
Advances in Mechanical Engineering
title A hybrid defect detection method for compact camera lens
title_full A hybrid defect detection method for compact camera lens
title_fullStr A hybrid defect detection method for compact camera lens
title_full_unstemmed A hybrid defect detection method for compact camera lens
title_short A hybrid defect detection method for compact camera lens
title_sort hybrid defect detection method for compact camera lens
url https://doi.org/10.1177/1687814017722949
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