Mura defect detection based on effective background reconstruction and contrast enhancement

A Mura defect detection method based on effective background reconstruction and contrast enhancement is proposed. Firstly, a new background reconstruction method based on defect region pre-elimination is proposed, which can effectively reconstruct the background image and eliminate the interference of uneven brightness. Then, the dual-gamma piecewise exponential transform method based on Otsu is introduced to enhance the difference image, which can effectively solve the problem of background residual and better enhance the contrast and contour of Mura region. Finally, the Mura defects can be separated quickly and accurately by using the dynamic threshold segmentation method. The experimental results show that, compared with the traditional polynomial surface fitting method and the discrete cosine transform method, the detection effect of this method for various types of Mura defects is stable, and the detection rate and no false alarm rate are more than 97% .