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An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager

Bin Yuan1, 2, Ping Gong1, Liang Xie1, 2, , Hui Wang1, Banghong Zhang1, Hui Gao1, 2 and Baokan Qi1, 2

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 Corresponding author: Liang Xie, Email: xiel@semi.ac.cn

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Abstract: In order to reduce the temperature measurement error with the uncooled infrared thermal imager, experiments were conducted to evaluate the effects of environment temperature and measurement distance on the measurement error of human eye temperature. First, the forehead temperature was used as an intermediate variable to obtain the actual temperature of human eyes. Then, the effects of environment temperature and measurement distance on the temperature measurement were separately analyzed. Finally, an empirical model was established to correlate actual eye temperature with the measured temperature, environment temperature, and measurement distance. To verify the formula, three different environment temperatures were tested at different distances. The measurement errors were substantially reduced using the empirical model for temperature correction. The results show that this method can effectively improve the accuracy of temperature measurement using the infrared thermal imager.

Key words: semiconductor deviceuncooled infrared thermal imagerenvironment temperaturemeasurement distanceerror correction



[1]
Tan J H, Ng E Y K, Rajendra A, et al. Infrared thermography on ocular surface temperature: A review. Infrared Phys Technol, 2009, 52(4): 97 doi: 10.1016/j.infrared.2009.05.002
[2]
Wang G, Wang W, Li K, et al. A digital thermometer with fast response and high precision. International Conference on Biomedical Engineering and Informatics, 2015: 504 doi: 10.1109/BMEI.2014.7002827
[3]
Jung A, Kalicki B, Zuber J, et al. Infrared thermal imaging as noninvasive method of body temperature measurement in hospitalized and nonhospitalised children. Przeglad Elektrotechniczny, 2013, 89(2): 99
[4]
Teunissen L P, Daanen H A. Infrared thermal imaging of the inner canthus of the eye as an estimator of body core temperature. J Med Eng Technol, 2011, 35(3–4): 134 doi: 10.3109/03091902.2011.554595
[5]
Rogalski A. Recent progress in infrared detector technologies. Infrared Phys Technol, 2011, 54(3): 136 doi: 10.1016/j.infrared.2010.12.003
[6]
Sun G C, Ha T J, Yu B G, et al. Improvement of uncooled infrared imaging detector by using mesoporous silica as a thermal isolation layer. Ceram Int, 2008, 34(4): 833 doi: 10.1016/j.ceramint.2007.09.088
[7]
Shen N, Tang Z A, Yu J, et al. A low-cost infrared absorbing structure for an uncooled infrared detector in a standard CMOS process. J Semicond, 2014, 35(3): 034014 doi: 10.1088/1674-4926/35/3/034014
[8]
Fu lo, G F. Uncooled nanoscale infrared high-speed sensors for missile seeker applications. Proc SPIE, 2007, 6542: 65421H doi: 10.1117/12.715005
[9]
Fraenkel R, Mizrahi U, Shtrichman I, et al. Cooled and uncooled infrared detectors for missile seekers. SPIE Defense + Security. 2014: 90700P
[10]
Meola C, Carlomagno G M. Recent advances in the use of infrared thermography. Meas Sci Technol, 2004, 15(9): R27 doi: 10.1088/0957-0233/15/9/R01
[11]
Huda A S N, Taib S. Application of infrared thermography for predictive/preventive maintenance of thermal defect in electrical equipment. Appl Therm Eng, 2013, 61(2): 220 doi: 10.1016/j.applthermaleng.2013.07.028
[12]
Calin M A, Mologhianu G, Savastru R, et al. A review of the effectiveness of thermal infrared imaging in the diagnosis and monitoring of knee diseases. Infrared Phys Technol, 2015, 69(8): 19 doi: 10.1016/j.infrared.2015.01.013
[13]
Rajmanova P, Nudzikova P, Vala D. Application and technology of thermal imagine camera in medicine. Ifac Papersonline, 2015, 48(4): 492 doi: 10.1016/j.ifacol.2015.07.083
[14]
Chiang L W, Guo S J, Chang C Y, et al. The development of a diagnostic model for the deterioration of external wall tiles of aged buildings in Taiwan. J Asian Architect Build Eng, 2016, 15(1): 111 doi: 10.3130/jaabe.15.111
[15]
Liu L, Ye Y T, Wu Y F, et al. Duration of startup of gaas wet etching measured by infrared-image of linear liquid film. J Semicond, 2007, 28(2): 222 (in Chinese) doi: 10.3321/j.issn:0253-4177.2007.02.016(inChinese)
[16]
Iwasaki Y, Misumi M, Nakamiya T. Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring. Sensors (Basel, Switzerland), 2013, 13(6): 7756 doi: 10.3390/s130607756
[17]
Zhang Y C, Chen Y M, Luo C. A method for improving temperature measurement precision on the uncooled infrared thermal imager. Measurement, 2015, 74: 64 doi: 10.1016/j.measurement.2015.07.016
[18]
Chrzanowski K. Influence of object-system distance on accuracy of remote temperature measurement with IR systems. Infrared Phys Technol, 1995, 36(3): 703 doi: 10.1016/1350-4495(94)00106-U
[19]
Zhang Y C, Chen Y M, Fu X B, et al. A method for reducing the influence of measuring distance on infrared thermal imager temperature measurement accuracy. Appl Therm Eng, 2016, 100: 1095 doi: 10.1016/j.applthermaleng.2016.02.119
Fig. 1.  Tested object imager in optical system.

Fig. 2.  (Color online) Picture of the infrared thermal imager.

Fig. 3.  Temperature distribution of the human face.

Fig. 4.  (Color online) Relationship between human forehead temper-ature and environment temperature.

Fig. 5.  (Color online) Forehead and eye temperatures measured by the uncooled infrared thermal imager.

Fig. 6.  (Color online) Measured temperature for various distances and environment temperatures.

Fig. 7.  (Color online) Fitting curves of measured temperature with environment temperature for various measurement distances.

Fig. 8.  (Color online) Curves of measured temperature, actual temperature, and corrected temperature in environment temperatures of (a) 10 °C, (b) 18 °C, and (c) 25 °C.

Table 1.   Measured eye temperature (°C) for various distances and environment temperatures.

T (°C) d (m)
0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8 5.4 6.0
22 34.95 34.89 34.75 34.71 34.56 34.36 34.27 34.17 34.15 33.94
23 35.35 35.23 35.00 34.85 34.72 34.66 34.56 34.46 34.30 34.16
24 35.64 35.56 35.41 35.21 35.11 34.97 34.86 34.74 34.60 34.63
25 35.86 35.79 35.69 35.54 35.46 35.21 35.05 35.05 34.84 34.74
26 36.27 36.27 35.99 35.93 35.92 35.74 35.60 35.61 35.52 35.44
DownLoad: CSV

Table 2.   Regression equations of measured eye temperature with measurement distance for various environment temperatures.

Temperature (°C) Regression equation* R2
22 TM = −0.188dd + 35.0928 0.98393
23 TM = −0.2092d + 35.4214 0.98364
24 TM = −0.2064d + 35.7544 0.98129
25 TM = −0.2191d + 36.0451 0.98489
26 TM = −0.1597d + 36.3556 0.95921
*: TM is the measured temperature and d is the measurement distance.
DownLoad: CSV

Table 3.   Regression equations of measured eye temperature with environment temperature for various measurement distances.

Distance (m) Regression equation* R2
0.6 TM = 0.315TU + 28.054 0.99015
1.2 TM = 0.332TU + 27.58 0.98937
1.8 TM = 0.317TU + 27.76 0.99526
2.4 TM = 0.313TU + 27.736 0.98
3.0 TM = 0.346TU + 26.85 0.97846
3.6 TM = 0.331TU + 27.044 0.98078
4.2 TM = 0.315TU + 27.308 0.97138
4.8 TM = 0.347TU + 26.478 0.97535
5.4 TM = 0.328TU + 26.81 0.92515
6.0 TM = 0.358TU + 25.99 0.94678
*: TM is the measured temperature and TU is the environment temperature.
DownLoad: CSV

Table 4.   Measurement error before correction.

Temperature (°C) 10 18 25
Max error (°C) 5.59 3.21 1.90
Average error (°C) 4.25 2.58 1.37
Max relative error (%) 16 9 5.2
DownLoad: CSV

Table 5.   Measurement error after correction.

Temperature (°C) 10 18 25
Max error (°C) 1.13 0.31 0.23
Average error (°C) 0.6 0.14 0.09
Max relative error (%) 3.2 0.8 0.62
DownLoad: CSV
[1]
Tan J H, Ng E Y K, Rajendra A, et al. Infrared thermography on ocular surface temperature: A review. Infrared Phys Technol, 2009, 52(4): 97 doi: 10.1016/j.infrared.2009.05.002
[2]
Wang G, Wang W, Li K, et al. A digital thermometer with fast response and high precision. International Conference on Biomedical Engineering and Informatics, 2015: 504 doi: 10.1109/BMEI.2014.7002827
[3]
Jung A, Kalicki B, Zuber J, et al. Infrared thermal imaging as noninvasive method of body temperature measurement in hospitalized and nonhospitalised children. Przeglad Elektrotechniczny, 2013, 89(2): 99
[4]
Teunissen L P, Daanen H A. Infrared thermal imaging of the inner canthus of the eye as an estimator of body core temperature. J Med Eng Technol, 2011, 35(3–4): 134 doi: 10.3109/03091902.2011.554595
[5]
Rogalski A. Recent progress in infrared detector technologies. Infrared Phys Technol, 2011, 54(3): 136 doi: 10.1016/j.infrared.2010.12.003
[6]
Sun G C, Ha T J, Yu B G, et al. Improvement of uncooled infrared imaging detector by using mesoporous silica as a thermal isolation layer. Ceram Int, 2008, 34(4): 833 doi: 10.1016/j.ceramint.2007.09.088
[7]
Shen N, Tang Z A, Yu J, et al. A low-cost infrared absorbing structure for an uncooled infrared detector in a standard CMOS process. J Semicond, 2014, 35(3): 034014 doi: 10.1088/1674-4926/35/3/034014
[8]
Fu lo, G F. Uncooled nanoscale infrared high-speed sensors for missile seeker applications. Proc SPIE, 2007, 6542: 65421H doi: 10.1117/12.715005
[9]
Fraenkel R, Mizrahi U, Shtrichman I, et al. Cooled and uncooled infrared detectors for missile seekers. SPIE Defense + Security. 2014: 90700P
[10]
Meola C, Carlomagno G M. Recent advances in the use of infrared thermography. Meas Sci Technol, 2004, 15(9): R27 doi: 10.1088/0957-0233/15/9/R01
[11]
Huda A S N, Taib S. Application of infrared thermography for predictive/preventive maintenance of thermal defect in electrical equipment. Appl Therm Eng, 2013, 61(2): 220 doi: 10.1016/j.applthermaleng.2013.07.028
[12]
Calin M A, Mologhianu G, Savastru R, et al. A review of the effectiveness of thermal infrared imaging in the diagnosis and monitoring of knee diseases. Infrared Phys Technol, 2015, 69(8): 19 doi: 10.1016/j.infrared.2015.01.013
[13]
Rajmanova P, Nudzikova P, Vala D. Application and technology of thermal imagine camera in medicine. Ifac Papersonline, 2015, 48(4): 492 doi: 10.1016/j.ifacol.2015.07.083
[14]
Chiang L W, Guo S J, Chang C Y, et al. The development of a diagnostic model for the deterioration of external wall tiles of aged buildings in Taiwan. J Asian Architect Build Eng, 2016, 15(1): 111 doi: 10.3130/jaabe.15.111
[15]
Liu L, Ye Y T, Wu Y F, et al. Duration of startup of gaas wet etching measured by infrared-image of linear liquid film. J Semicond, 2007, 28(2): 222 (in Chinese) doi: 10.3321/j.issn:0253-4177.2007.02.016(inChinese)
[16]
Iwasaki Y, Misumi M, Nakamiya T. Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring. Sensors (Basel, Switzerland), 2013, 13(6): 7756 doi: 10.3390/s130607756
[17]
Zhang Y C, Chen Y M, Luo C. A method for improving temperature measurement precision on the uncooled infrared thermal imager. Measurement, 2015, 74: 64 doi: 10.1016/j.measurement.2015.07.016
[18]
Chrzanowski K. Influence of object-system distance on accuracy of remote temperature measurement with IR systems. Infrared Phys Technol, 1995, 36(3): 703 doi: 10.1016/1350-4495(94)00106-U
[19]
Zhang Y C, Chen Y M, Fu X B, et al. A method for reducing the influence of measuring distance on infrared thermal imager temperature measurement accuracy. Appl Therm Eng, 2016, 100: 1095 doi: 10.1016/j.applthermaleng.2016.02.119
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    Received: 21 December 2017 Revised: 22 March 2018 Online: Uncorrected proof: 16 May 2018Accepted Manuscript: 05 July 2018Published: 01 September 2018

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      Bin Yuan, Ping Gong, Liang Xie, Hui Wang, Banghong Zhang, Hui Gao, Baokan Qi. An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager[J]. Journal of Semiconductors, 2018, 39(9): 094008. doi: 10.1088/1674-4926/39/9/094008 B Yuan, P Gong, L Xie, H Wang, B H Zhang, H Gao, B K Qi, An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager[J]. J. Semicond., 2018, 39(9): 094008. doi: 10.1088/1674-4926/39/9/094008.Export: BibTex EndNote
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      Bin Yuan, Ping Gong, Liang Xie, Hui Wang, Banghong Zhang, Hui Gao, Baokan Qi. An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager[J]. Journal of Semiconductors, 2018, 39(9): 094008. doi: 10.1088/1674-4926/39/9/094008

      B Yuan, P Gong, L Xie, H Wang, B H Zhang, H Gao, B K Qi, An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager[J]. J. Semicond., 2018, 39(9): 094008. doi: 10.1088/1674-4926/39/9/094008.
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      An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager

      doi: 10.1088/1674-4926/39/9/094008
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      Projected supported by the National Key Research and Development Program of China (No. 2016YFD0500903) and the National Natural Science Foundation of China (Nos. 61501422, 61705218).

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      • Corresponding author: Email: xiel@semi.ac.cn
      • Received Date: 2017-12-21
      • Revised Date: 2018-03-22
      • Published Date: 2018-09-01

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