Detection and classification of painting defects by image processing and machine learning using low-cost hardware

• Grant number: 21/00367-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2021
• End date: September 30, 2022
• Field of knowledge: Engineering - Mechanical Engineering - Manufacturing Processes
• Principal Investigator: Gustavo Franco Barbosa
• Grantee: José Oliveira Cruz Neto
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Due to the current technological and scientific advancement in the industrial context, the quality standard of the products has been increasingly demanded, and the visual aspect has become a determining feature in the commercial success of a brand or product. Therefore, the automation of quality inspection procedures is highly requested, especially in the automotive sector, where the inspection of paint quality is still done visually by an experienced worker in the area.Then, this work aims to create an algorithm for identifying defects in paintings that can be used in low-cost hardware and makes up one of the steps in the automation of painting inspection.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PEREIRA, FRANCO ROCHA; RODRIGUES, CAIO DIMITROV; DA SILVA E SOUZA, HUGO; NETO, JOSE OLIVEIRA CRUZ; ROCHA, MATHEUS CHIARAMONTE; BARBOSA, GUSTAVO FRANCO; SHIKI, SIDNEY BRUCE; INOUE, ROBERTO SANTOS. Force and vision-based system for robotic sealing monitoring. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v. N/A, p. 13-pg., 2023-02-27. (19/22115-0, 21/00367-8, 21/00745-2)