%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/09.02.21.25
%2 sid.inpe.br/sibgrapi/2016/09.02.21.25.35
%T Detecção Automática de Microcomponentes SMT Ausentes em Placas de Circuito Impresso
%D 2016
%A Rocha, Cleandro de Souza,
%A Menezes, Mathias Afonso Guedes de,
%A Oliveira, Felipe Gomes de,
%@affiliation Federal University of Amazoas
%@affiliation Federal University of Amazonas
%@affiliation Federal University of Amazonas
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K Visão de Máquina, Aprendizado de Máquina, Inspeção Industrial, Controle de Qualidade.
%X This work presents a visual inspection approach to detect absence/presence of surface mount components (SMC) on printed circuit boards (PCB). We propose a methodology based on the combination of Machine Vision and Machine Learning to detect component absence, with more quality and precision, using noised digital images acquired directly from PCB industrial production line. The applicability of method was tested for automatic visual inspection in motherboards, where the demand of these components is high. The results obtained demonstrates the robustness of our methodology in images with high levels of gaussian and salt and pepper noise, obtaining 97.25% of hit rate.
%@language pt
%3 Sibgrapi2016_CameraReady.pdf