TY - GEN
T1 - Analytical analysis of adaptive defect detection in amplitude and phase structures using photorefractive four-wave mixing
AU - Nehmetallah, George
AU - Donoghue, John
AU - Banerjee, Partha
AU - Khoury, Jed
AU - Yamamoto, Michiharu
AU - Peyghambarian, Nasser
N1 - Publisher Copyright:
© 2016 SPIE.
PY - 2016
Y1 - 2016
N2 - In this work, brief theoretical modeling, analysis, and novel numerical verification of a photorefractive polymer based four wave mixing (FWM) setup for defect detection has been developed. The numerical simulation helps to validate our earlier experimental results to perform defect detection in periodic amplitude and phase objects using FWM. Specifically, we develop the theory behind the detection of isolated defects, and random defects in amplitude, and phase periodic patterns. In accordance with the developed theory, the results show that this technique successfully detects the slightest defects through band-pass intensity filtering and requires minimal additional post image processing contrast enhancement. This optical defect detection technique can be applied to the detection of production line defects, e.g., scratch enhancement, defect cluster enhancement, and periodic pattern dislocation enhancement. This technique is very useful in quality control systems, production line defect inspection, and computer vision.
AB - In this work, brief theoretical modeling, analysis, and novel numerical verification of a photorefractive polymer based four wave mixing (FWM) setup for defect detection has been developed. The numerical simulation helps to validate our earlier experimental results to perform defect detection in periodic amplitude and phase objects using FWM. Specifically, we develop the theory behind the detection of isolated defects, and random defects in amplitude, and phase periodic patterns. In accordance with the developed theory, the results show that this technique successfully detects the slightest defects through band-pass intensity filtering and requires minimal additional post image processing contrast enhancement. This optical defect detection technique can be applied to the detection of production line defects, e.g., scratch enhancement, defect cluster enhancement, and periodic pattern dislocation enhancement. This technique is very useful in quality control systems, production line defect inspection, and computer vision.
KW - Pattern recognition
KW - defect detection
KW - four-wave mixing
KW - photorefractive material
UR - http://www.scopus.com/inward/record.url?scp=84983087105&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983087105&partnerID=8YFLogxK
U2 - 10.1117/12.2221911
DO - 10.1117/12.2221911
M3 - Conference contribution
AN - SCOPUS:84983087105
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Optical Pattern Recognition XXVII
A2 - Casasent, David
A2 - Alam, Mohammad S.
PB - SPIE
T2 - Optical Pattern Recognition XXVII
Y2 - 20 April 2016 through 21 April 2016
ER -