A Statistical Framework for Geometric
نویسندگان
چکیده
An image is never noise free. Visual inspection of a part from its image is therefore aaected by image errors. Understanding how image errors aaect measurement precision is therefore critical for accurate inspection. Existing visual inspection methods either setup a highly controlled environment to minimize image errors or simply ignore image errors. They therefore suuer from limited accuracy and lack of robustness. In this paper, we lay out a statistical framework that allows to explicitly handle image errors and characterize their impact on measurement precision. A hierarchical model is also proposed to model manufacturing and measurement errors. Based on the model, a Bayesian technique is introduced to statistically infer the geometric tolerances of a manufactured part.
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