A framework to develop intelligent system for measuring product features using open CV technique

• Main Authors: Saif, Yazid, Yusof, Yusri, Ahmed, Maznah lliyas, Pathan, Zohaib khan, Latif, Kamran, Abdul Kadir, Aini Zuhra
• Format: Article
• Language: English
• Published: School of Technology Management & Logistics 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/28099/1/JTOM%2015%202%202020%2042%2051.pdf; http://repo.uum.edu.my/28099/; http://e-journal.uum.edu.my/index.php/jtom

This research aims to propose an innovative framework using ISO14649 standard to detect defects in manufactured shaped objects or geometric surfaces of non-linear products of the CNC machine. The significant importance in order to recognize the potential to improve industry product quality inspection and encourage the waste of timing machines and product rejection. Open Computer Vision (Open CV) offers a smart, non-contact measurement and cost-effective technique to fulfill the requirements. The framework depends on the new technique of Open CV, which includes two parts: an intelligent selection of work-piece capturing the image for a particular inspection of the planar interfaces such as the hole, rectangular, pocket one, and the symmetric lighting model comparison approach for measurement of defects in the matched images. The contribution of this study is to build a structure in the computer vision method with a convolution neural network that predicts the classification of the feature for better accuracy and emphasizes the significant characteristics of the image processing technique coupled with experimental data on demanding image datasets and quality inspection measures.