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

Grant number: 21/00367-8
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2021
Effective date (End): September 30, 2022
Field of knowledge:Engineering - Mechanical Engineering - Manufacturing Processes
Principal researcher:Gustavo Franco Barbosa
Grantee:José Oliveira Cruz Neto
Home 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.

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