A new algorithm on the automatic TFT‐LCD mura defects inspection based on an effective background reconstruction. Issue 12 (11th February 2018)

• Record Type: Journal Article
• Authors: Ngo, Chinh; Park, Yong Jin; Jung, Jeehyun; Hassan, Rizwan Ul; Seok, Jongwon
• Is Part Of: Journal of the Society for Information Display. Volume 25:Issue 12(2017)
• Page Start: 737
• Page End: 752
• Publication Date: 2018-02-11
• Subjects: mura defect -- TFT‐LCD -- image processing -- background reconstruction; Information display systems -- Periodicals; 621.38154205
• DOI: 10.1002/jsid.622
• Languages: English
• ISSNs: 1071-0922

Abstract

Abstract: In this study, an automatic detection method for mura defects is developed based on an accurate reconstruction of the background and precise evaluation of the mura index level. To achieve this, an effective background reconstruction method is first developed to represent the brightness intensity of the display panel. As a result, any nonuniform brightness of the background can be removed effectively. Furthermore, the associated mura level is quantified based on the sensitivity of the human eye in order to alternatively grade the liquid‐crystal display panels. The main focus of this study is on the reconstruction of the background from the display under test image. The proposed method takes full advantage of the following three existing methods: low‐pass filtering, discrete cosine transform, and polynomial surface fitting. By applying the method to several case studies, we have shown that it is more effective compared with other existing methods in detecting various types of mura defects. Abstract : We developed an algorithm to adaptively reconstruct the background image with high accuracy and a highly efficient computation process for the entire mura detection. We applied the reconstructed background to the image segmentation process based on the sensitivity of the human eye. We finally validated the proposed method by comparing the results obtained with those of previous studies.