Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Proceeding Applied Business and Engineering Conference
Imam Mulyono
Politeknik Negeri Batam
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Identifikasi Label Kode Pipa pada Sistem Konveyor untuk Pipe Handling Berbasis Template Matching Imam Mulyono; Iman Fahruzi
ABEC Indonesia Vol. 10 (2022): 10th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Nowadays, technological advancements are growing need for computer programs that might benefitindustrial purposes. Image recognition is crucial in technological advancements spanning from medical demandsto security and other industries. One of them is the necessity in the oil and gas industry for a computerapplication that can recognize pipe code labels, particularly in pipe handling. Because of the requirement forproduction assistance, to recognize the pipe code label image, an NI Vision control system was built. There arenumerous stages of label identification in this study, including taking photographs with a webcam camera(capture), cropping, grayscale, and saving data. The system can provide an accuracy of 88% based on test resultson 25 samples of ¾ inch PVC pipe code labels with a camera distance to the pipe code label field of 85 cm, 493color weights, and an optimal score level of 75%.
Co-Authors Iman Fahruzi