TY - JOUR ID - 2408 TI - Automatic Visual Inspection System based on Image Processing and Neural Network for Quality Control of Sandwich Panel JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Torkzadeh, V. AU - Toosizadeh, S. AD - Department of Computer Engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran. Y1 - 2022 PY - 2022 VL - 10 IS - 2 SP - 217 EP - 231 KW - Sandwich panel KW - Dipping KW - Buckling KW - Image Processing KW - Convolutional neural network DO - 10.22044/jadm.2022.11002.2247 N2 - In this study, an automatic system based on image processing methods using features based on convolutional neural networks is proposed to detect the degree of possible dipping and buckling on the sandwich panel surface by a colour camera. The proposed method, by receiving an image of the sandwich panel, can detect the dipping and buckling of its surface with acceptable accuracy. After a panel is fully processed by the system, an image output is generated to observe the surface status of the sandwich panel so that the supervisor of the production line can better detect any potential defects at the surface of the produced panels. An accurate solution is also provided to measure the amount of available distortion (depth or height of dipping and buckling) on the sandwich panels without needing expensive and complex equipment and hardware. UR - https://jad.shahroodut.ac.ir/article_2408.html L1 - https://jad.shahroodut.ac.ir/article_2408_bf3fccbd541515278bd8cf1b39d7c578.pdf ER -