TY - JOUR
T1 - Optimization Method of IR Thermography Facial Image Registration
AU - Jian, Bo Lin
AU - Chen, Chieh Li
AU - Lin, Chih Jer
AU - Yau, Her Terng
N1 - Funding Information:
This work was supported in part by the Ministry of Science and Technology of the Republic of China, Taiwan, under Contract MOST 107-2218-E-167 -004.
Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - So far, there have been many types of researches subject to technical requirements due to image registration. Using image registration can lower deviation from sequential images and make it possible to analyze the information variation of the particular area subsequently. This study provides a procedure creating fixed image based on the data of facial IR thermography, where its methods include the visual saliency map by detected image, as well as cluster algorithm. Comparison is also made here to solve the merits and demerits by affine parameter to reach the optimum measure among Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing Algorithm, where there are two control parameters concerning this experiment: one is the calculation of time confined each alignment, while the other one is to use parallel computing toolbox or not. The optimum method will be chosen by the values of the objective function based on the control parameters. Afterward, the optimal internal parameter is to be verified through the Taguchi experiment and the validity of this procedure in this study will be built following the parameter result as above. Therefore, the difference of images before and after alignment can be validated by overlapping the images before and after alignment as well as the image quality measurements, where its results reveal that the alignment procedure of IR thermography in this study is capable of performing human face alignment precisely, and subsequently, do help data statistics and analysis concerning temperature area interdependence.
AB - So far, there have been many types of researches subject to technical requirements due to image registration. Using image registration can lower deviation from sequential images and make it possible to analyze the information variation of the particular area subsequently. This study provides a procedure creating fixed image based on the data of facial IR thermography, where its methods include the visual saliency map by detected image, as well as cluster algorithm. Comparison is also made here to solve the merits and demerits by affine parameter to reach the optimum measure among Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing Algorithm, where there are two control parameters concerning this experiment: one is the calculation of time confined each alignment, while the other one is to use parallel computing toolbox or not. The optimum method will be chosen by the values of the objective function based on the control parameters. Afterward, the optimal internal parameter is to be verified through the Taguchi experiment and the validity of this procedure in this study will be built following the parameter result as above. Therefore, the difference of images before and after alignment can be validated by overlapping the images before and after alignment as well as the image quality measurements, where its results reveal that the alignment procedure of IR thermography in this study is capable of performing human face alignment precisely, and subsequently, do help data statistics and analysis concerning temperature area interdependence.
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U2 - 10.1109/ACCESS.2019.2927747
DO - 10.1109/ACCESS.2019.2927747
M3 - Article
AN - SCOPUS:85073891559
SN - 2169-3536
VL - 7
SP - 93501
EP - 93510
JO - IEEE Access
JF - IEEE Access
M1 - 8758960
ER -