Cascade quick image defect segmentation method

The invention relates to a cascade quick image defect segmentation method. The method includes: preprocessing an image to acquire global threshold information, and performing rough image segmentation based on a global adaptive threshold; acquiring fine image segmentation through priori knowledge and a level set method of local image information; eliminating evident error candidate defects and error alarms by means of size and shape analysis, and performing target separation on the basis of a parameterized mathematical morphology method. the problems such that non-uniformity of local and global thresholds leads to inaccurate image segmentation are solved by means of a stratified strategy; features of defects, such as shape and size, are introduced to a level set energy function; the priori knowledge of the defect shape is fully utilized, the problem of initial dependence is solved, and the method is well applicable to image defect segmentation having shape features; by introducing the cascade image processing architecture and discarding most non-defective images from the most front, unbalance of data distribution is greatly relieved, and defect segmentation speed and precision is greatly improved.