Microsurface Defect Recognition via Microlaser Line Projection and Affine Moment Invariants

Advanced non-destructive techniques play an important role in detecting surface defects in the context of additive manufacturing, with non-destructive technologies providing surface data for the recognition of surface defects. In this line, it is necessary to implement microscope vision technology for the inspection of surface defects. This study proposes an approach for microsurface defect recognition using affine moment invariants based on microlaser line contouring, allowing for the detection of microscopic holes and scratches. For this purpose, the surface is represented by a Bezier surface to characterize microsurface defects through patterns of affine moment invariants after the surface is contoured via microlaser line projection. In this way, microholes and scratches can be recognized by computing a pattern of affine moment invariants for each region of the target surface. This technique is performed using a microscope vision system, which retrieves the surface topography via microlaser line scanning. The proposed technique allows for the recognition of holes and scratches with a surface depth greater than 20 microns, with a minor relative error of less than 2%. The proposed surface defect recognition approach enhances the literature on recognition techniques performed using visual technologies based on optical microscope systems. This contribution is corroborated through a discussion focused on the recognition of holes and scratches by means of various optical-microscope-based systems.