LCD mura detection with multi-image accumulation and multi-resolution background subtraction

Din Chang Tseng, You Ching Lee, Cheng En Shie

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We integrated the techniques of multi-image accumulation and multi-resolution background subtraction to detect mura defects in low-contrast and high-noised TFT-LCD images. First, several images of an LCD on a moving product conveyer are contiguously captured and then a synthesized LCD image is used to calibrate the non-uniform illumination of these images. Second, the images are aligned in position to accumulate the gray levels of the pixels which all correspond to a point on the LCD. The multi-image accumulation process enhances the contrast between the mura defects and the background; moreover, visible mura problems due to the view angle and the uneven illumination are also mostly resolved. Third, the multi-resolution backgrounds of the accumulated image are progressively estimated based on the discrete wavelet transform (DWT) and the defect candidates are extracted coarse-to-fine and accumulated by subtracting the background from the accumulated image. The multi-resolution background subtraction strategy speeds the detection process and solves the problem of different sizes of mura defects without reducing the detection rate. Finally, a standard thresholding method is used to "threshold out" the mura defects. The stability and effect of the proposed method are demonstrated in experiments.

Original languageEnglish
Pages (from-to)4837-4850
Number of pages14
JournalInternational Journal of Innovative Computing, Information and Control
Issue number7 A
StatePublished - Jul 2012


  • Automatic optical inspection
  • Multi-image accumulation
  • Multi-resolution background subtraction
  • Mura detection


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