Paper Info
Title
Dead Pixel Detection on Liquid Crystal Displays using Random Forest, SVM, and Harris Detector
Abstract
Manufacturing TVs and monitors requires an effective method to detect the dead pixels. These defects are usually identified by operators manually. However, manual inspection is susceptible to failure due to human fatigue and generate a high cost for production process. In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we propose three methods for automated detection of dead pixels. Two proposed methods were based on machine learning (ML) techniques, random forest (RF) and support vector machine (SVM) algorithms. The third method was based in digital image processing (DIP), Harris algorithm. As result, the SVM obtained the better performance with 92.1% of precision in two of three used image database.
Year
DOI
Venue
2020
10.1109/ICCE-Taiwan49838.2020.9258171
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
Keywords
DocType
ISSN
machine learning techniques,random forest algorithm,support vector machine algorithm,SVM,liquid crystal displays,Harris detector,manufacturing TVs,manual inspection,human fatigue,production process,automated dead pixel detection
Conference
2575-8276
ISBN
Citations 
PageRank 
978-1-7281-7400-6
0
0.34
References 
Authors
0
19
Name
Order
Citations
PageRank
David A.O. Ferreira100.34
Diego A. Amoedo200.68
Luciana R. Costa300.68
Myke D.M. Valadao400.34
Adriana S. Souza500.68
Kethilen Y. Ouchi600.34
Antonio M.C. Pereira700.34
Gustavo M. Torres800.34
Mateus O. Silva900.34
Caio F.S. Cruz1000.34
Agemilson P. Silva1100.68
Ruan J.S. Belem1200.34
Anderson S. Jesus1300.68
Andre S. Costa1400.34
Lucas G.C. Evangelista1500.34
Osmar R.A. Silva1600.34
Thiago B. Bezerra1700.68
Waldir S.S. Junior1800.34
Celso B. Carvalho1900.68