Open AccessResearch on SSD Countersink Defect Detection Method Based on Machine Vision
Author(s) -
Lifeng Dang,
Zuo Wen-yan,
Qin Shi
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/632/4/042068
Subject(s) - computer science , artificial intelligence , computer vision , object detection , false positive rate , machine vision , fault detection and isolation , image processing , image (mathematics) , pattern recognition (psychology) , actuator
Defect detection of counterbore plays an important role in SSD solid state disk panel automatic detection. Its goal is to accurately find and locate the defect location. At present, the detection of counterbores mostly adopts manual detection, which has the problems of low detection speed, high false detection rate and high missed detection rate. In this paper, the defect detection algorithm of counterbore is studied. After experimental verification, the improved algorithm expansion ⊕ closed operation and Blob analysis tools are finally used for image processing to ensure the integrity of the detection effect and further improve the accuracy of SSD counterbore detection.