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A statistical framework for geometric tolerancing manufactured parts

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2 Author(s)
Qiang Ji ; Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA ; Haralick, R.M.

Visual inspection of a part from its image is always affected by image errors. Understanding how image errors affect measurement precision is therefore critical for accurate inspection. In this paper we lay out a statistical framework that allows one 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

Published in:

Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on  (Volume:2 )

Date of Conference:

16-20 Aug 1998

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