The application discloses an aluminum
alloy floor protective layer defect image recognition method and
system, relates to the technical field of
computer vision image recognition, and comprises several function modules, including: a three-dimensional morphology pre-
perception module, which obtains three-dimensional
point cloud data of the surface of an aluminum
alloy floor protective layer, calculates a local normal vector and a high
light reflection risk coefficient, and divides a
field of view into a low-curvature area and a high-curvature area to be scanned based on the high
light reflection risk coefficient; an adaptive polarization regulation and control imaging module, which calculates an optimal
extinction angle for the low-curvature area according to the local normal vector, fixes a detection angle, collects a
single frame of polarized image, performs detection angle gradual scanning with the optimal
extinction angle as the center for the high-curvature area to be scanned, and collects a plurality of polarized image sequences; and a multi-frame polarization fusion and defect enhancement module, which establishes a
physical model of
light intensity change with a detection angle for a plurality of polarized image sequences pixel by pixel, and separates a non-polarized
light intensity component image and a
polarization modulation amplitude image through fitting.