Image processing: the nature and value of fuzzy metrology

H. John Caulfield

doi:10.1117/12.799682

3 September 2008 Image processing: the nature and value of fuzzy metrology

H. John Caulfield

Proceedings Volume 7071, An Optical Believe It or Not: Key Lessons Learned; 70710H (2008) https://doi.org/10.1117/12.799682
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

The term "fuzzy metrology" is almost as misleading as the term "fuzzy logic." Many people simply avert their eyes from fuzzy logic, because they know (correctly) that good logic is not fuzzy but rigorous. But, neither the measured result nor the logic itself is fuzzy in any conventional sense. Many sets are fuzzy, so they must be handled not by crisp logic but by fuzzy logic. Fuzzy logic itself is quite rigorous. Likewise, fuzzy metrology uses the mechanisms of fuzzy logic to arrive at precise measurements of physical things. In itself it is rigorous. You avert your eyes at your peril. After a general discussion of the basics of fuzzy logic, I show a number of examples that allow the user even better understanding of when fuzzy metrology might be superior to conventional crisp metrology.

Citation Download Citation

H. John Caulfield "Image processing: the nature and value of fuzzy metrology", Proc. SPIE 7071, An Optical Believe It or Not: Key Lessons Learned, 70710H (3 September 2008); https://doi.org/10.1117/12.799682

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