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Mura is a typical vision defect of LCD panel, appearing as local lightness variation with low contrast and blurry contour. This letter presents a new machine vision inspection way for Mura defect based on the level set method. First, a set of real Gabor filters are applied to eliminating the global textured backgrounds. Then, the level set method is employed for image segmentation with a new region-based active contours model, which is an improvement of the Chan-Vese's model so that it more suitable to the segmentation of Mura. Using some results from the level set based segmentation, the defects are quantified based on the SEMU method. Experiments show that the proposed method has better performance for Mura detection and quantification.