Automatic mura inspection using the principal component analysis for the TFT-LCD panel

Jim Woo Yun, Heon Gu, Dae Hwan Kim, Hoi Sik Moon, Sung Jea Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper, we propose a principal component analysis (PCA)-based mura detection algorithm. Recent conventional algorithms divide the panel image with the detection window and detect the mura in each detection window. However, these algorithms have several problems due to the limitation of the detection window size. To overcome these problems, we first estimate the background image of the entire panel image by applying the PCA method. And then, the difference image between the input panel image and the estimated background image is used for the mura region decision. The experimental results show that the proposed algorithm outperforms the conventional mura detection algorithm.

Original languageEnglish
Title of host publicationDigest of Technical Papers - IEEE International Conference on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages109-110
Number of pages2
ISBN (Electronic)9781479938308
DOIs
Publication statusPublished - 2014 Sept 18
Event1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014 - Taipei, Taiwan, Province of China
Duration: 2014 May 262014 May 28

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Other

Other1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014
Country/TerritoryTaiwan, Province of China
CityTaipei
Period14/5/2614/5/28

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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