Machine vision system for curved surface inspection

This application-oriented paper discusses a noncontact 3D range data measur ement system to improve the performance of the existing 2D herring roe grad ing system. The existing system uses a single CCD camera with unstructured halogen lighting to acquire and analyze the shape of the 2D shape of the he rring roe for size and deformity grading. Our system will act as an additio nal system module, which can be integrated into the existing 2D grading sys tem, providing the additional third dimension to detect deformities in the herring roe, which were not detected in the 2D analysis. Furthermore, the a dditional surface depth data will increase the accuracy of the weight infor mation used in the existing grading system. In the proposed system, multipl e laser light stripes are projected into the herring roe and the single B/W CCD camera records the image of the scene. The distortion in the projected line pattern is due to the surface curvature and orientation. Utilizing th e linear relation between the projected line distortion and surface depth, the range data was recovered from a single camera image. The measurement technique is described and the depth information is obtaine d through four steps: (1) image capture, (2) stripe extraction, (3) stripe coding, (4) triangulation, and system calibration. Then, this depth informa tion can be converted into the curvature and orientation of the shape for d eformity inspection, and also used for the weight estimation. Preliminary results are included to show the feasibility and performance of our measurement technique. The accuracy and reliability of the computerize d herring roe grading system can be greatly improved by integrating this sy stem into existing system in the future.