| 摘要 |
Image processing system using cameras and image processing techniques to identify undesirable objects on roller conveyor lines. The cameras above the conveyor capture images of the passing objects. The roller background information is removed and images of the objects remain. To analyze each individual object accurately, the adjacent objects are isolated and small noisy residue fragments are removed. A spherical optical transform and a defect preservation transform preserve any defect levels on objects even below the roller background and compensate for the non-lambertian gradient reflectance on spherical objects at their curvatures and dimensions. Defect segments are then extracted from the resulting transformed images. The size, level, and pattern of the defect segments indicate the degree of defects in the object. The extracted features are fed into a recognition process and a decision making system for grade rejection decisions. The locations in coordinates of the defects generated by a defect allocation function are combined with defect rejection decisions and user parameters to signal appropriate mechanical actions such as to separate objects with defects from those that are defect-free.
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