An Automatic Optical Inspection Algorithm of Capacitor Based on Multi-angle Classification and Recognition

Author:

Fang Jian,Shang Lina,Xiong Kai,Gao Guangchun,Zhang Cui

Abstract

Abstract There are many plug-in components in PCB circuit production. The AOI of these components has always been a difficult problem because of the large deviation of manual installation position of these components. In this paper, an AOI algorithm based on multi-angle classification and recognition is proposed for the plug-in polar capacitors. The algorithm combines traditional image comparison method with feature recognition method, and uses AdaBoost classifier based on Haar-like feature to recognize and classify multi-angle polar capacitors. Experimental results show that the algorithm proposed in this paper can effectively detect three kinds of defects: capacitor missing, capacitor polarity error and capacitor size mismatch.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference7 articles.

1. Guidelines of Automated Optical Inspection (AOI) System Development;Hsien-Chou,2018

2. Pack Hsieh, Classification of Solder Joints via Automatic Mistake Reduction System for Improvement of AOI Inspection;Yi-Ming,2018

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4. Development of SBC based Machine-Vision System for PCB Board Assembly Automatic Optical Inspection;Ardhy,2016

5. Development Of Techniques to Determine Object Shifts for PCB Board Assembly Automatic Optical Inspection (AOI);Resa,2018

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