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

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.

Evaluation of facial temperature distribution changes during meditation using infrared thermal imaging:An experimental,cross-over study

Objective:To investigate the differences between meditation and resting states using infrared thermal imaging(IRTI)to determine facial temperature distribution features during meditation and annotate the patterns of facial temperature changes during meditation from the perspective of traditional Chinese medicine facial diagnosis.Methods:Each participant performed 10 min meditation and 10 min resting but in different sequences.A concentration test was set as the task load,followed by a meditation/resting or resting/meditation session,during which the participants'facial temperatures were observed using IRTI.Participants were scored on the Big Five Inventory(BFI)and Mindful Attention Awareness Scale(MAAS).Results:Forehead temperatures decreased more during meditation than during the resting state.The chin temperature increased only during meditation(P<.0001).For the subjects with meditation experience,there were significant differences in the temperatures of the left forehead(P<.01),right forehead(P<.01)and chin(P<.05)between the meditation and resting state at the 10~(th)min.In the nontask state,the BFI-Extraversion showed a negative correlation with the temperature of the left forehead(R=-0.41,P=.03).In the post-task state,the temperature of the left forehead was negatively correlated with scores on the MAAS(R=-0.42,P=.02).Conclusion:Using IRTI to study meditation offers a practical solution to the challenges in meditation research.The results indicate that an increase in chin temperature may be a representative feature of a meditation state,and forehead temperature is also a potential indicator.

Utilization of Thermal Infrared Image for Inversion of Winter Wheat Yield and Biomass

The present paper utilizes thermal infrared image for inversion of winter wheat yield and biomass with different technology of irrigation(drip irrigation,sprinkler irrigation,flood irrigation).It is the first time that thermal infrared image is used for predicting the winter wheat yield and biomass.The temperature of crop and background was measured by thermal infrared image.It is necessary to get the crop background separation index(CBSIL,CBSIH),which can be used for distinguishing the crop value from the image.CBSIL and CBSIH(the temperature when the leaves are wet adequately;the temperature when the stomata of leaf is closed completely) are the threshold values.The temperature of crop ranged from CBSIL to CBSIH.Then the ICWSI was calculated based on relevant theoretical method.The value of stomata leaf has strong negative correlation with ICWSI proving the reliable value of ICWSI.In order to construct the high accuracy simulation model,the samples were divided into two parts.One was used for constructing the simulation model,the other for checking the accuracy of the model.Such result of the model was concluded as:(1) As for the simulation model of soil moisture,the correlation coefficient(R2) is larger than 0.887 6,the average of relative error(Er) ranges from 13.33% to 16.88%;(2) As for the simulation model of winter wheat yield,drip irrigation(0.887 6,16.89%,-0.12),sprinkler irrigation(0.970 0,14.85%,-0.12),flood irrigation(0.969 0,18.87%,0.18),with the values of R2,Er and CRM listed in the parentheses followed by the individual term.(3) As for winter wheat biomass,drip irrigation(0.980 0,13.70%,0.13),sprinkler irrigation(0.95,13.15%,-0.14),flood irrigation(0.970 0,14.48%,-0.13),and the values in the parentheses are demonstrated the same as above.Both the CRM and Er are shown to be very low values,which points to the accuracy and reliability of the model investigated.The accuracy of model is high and reliable.The results indicated that thermal infrared image can be used potentially for inversion of winter wheat yield and biomass.

INFRARED THERMAL IMAGE STUDY ON THE FOREWARNING OF COAL AND SANDSTONE FAILURE UNDER LOAD

In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone failure under load have three kinds of infrared thermal features as well as infrared forewarning messages. That are: (1) temperature rises gradually but drops before failure ; (2) temperature rises gradually but quickly rises before failure; (3) first rises,then drops and lower temperature emerges before failure. The further researches and the prospect of micro-wave remote sensing detection .on ground pressure is also discussed.

Analysis of Nuclear Track Parameters of CN-85 Detector Irradiated to Thermal Neutrons by Using MATLAB Program

CN-85 detector which covered with boric acid H3Bo3 pellete has been irradiated by thermal neutrons from (241Am-9Be) source with activity 12 Ci and neutron flux 105 n. cm-2. s-1. The irradiation times-TD for detector were 4 h, 8 h, 16 h and 24 h. The track detector has been etched with sodium hydroxide. After chemical etching of the irradiated CN-85 detector, the images have been taken from a digital camera connected to the optical microscope. Image processing for the output images has been performed using MATALB program, and these images were analyzed and we had found the following relations: a) The relation between summation of opened track or surface density for tracks (intensity-IT) varies with radius of opening (track radius-RT). b) The relation between the tracks number-NT varies with the tracks diameter-DT (in micrometer) and tracks area-AT. That analysis of image processing was obtained, and the track intensity-IT was decreased with increase of track radius-RT at all of the irradiation time-TD. And the track intensity-IT was increased with increasing irradiation time-TD (h) for different track radius-RT (0.4225, 0.845, 1.2675 and 1.69 μm). The study indicates the possibility of using the analysis of image processing to CN-85 detector for classification of α-particle emitters through limitation of radius of track-RT, in addition to the contribution of these techniques in preparation of nano-filters and nono-membrane in nanotechnology fields.

Improving wavelet reconstruction algorithm to achieve comprehensive application of thermal infrared remote sensing data from TM and MODIS

According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under the domain of neighborhood wavelet reconstruction, data of TM and MO DIS are divided into three layers using wavelet decomposition. The texture information of TM data is retained by fusing highfrequency information. The neighborhood correction coefficient method （NC CM） is set up based on the search neighborhood of a certain size to fuse lowfrequency information. Thermal infrared value of MODIS data is reduced to the space value of TM data by applying NCCM. The data with high spectrum, high spatial and high temporal resolution, are obtained through the al gorithm in the paper. Verification results show that the texture information of TM data and high spec tral information of MODIS data could be preserved well by the fusion algorithm. This article could provide technical support for high precision and fast extraction of the surface environment parame ters.

Heat transfer and temperature evolution in underground mininginduced overburden fracture and ground fissures: Optimal time window of UAV infrared monitoring

Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle(UAV) infrared imager. In this study, discrete element software UDEC was employed to investigate the overburden fracture field under different mining conditions. Multiphysics software COMSOL were employed to investigate heat transfer and temperature evolution of overburden fracture and ground fissures under the influence of mining condition, fissure depth, fissure width, and month alternation. The UAV infrared field measurements also provided a calibration for numerical simulation. The results showed that for ground fissures connected to underground goaf(Fissure Ⅰ), the temperature difference increased with larger mining height and shallow buried depth. In addition, Fissure Ⅰ located in the boundary of the goaf have a greater temperature difference and is easier to be identified than fissures located above the mining goaf. For ground fissures having no connection to underground goaf(Fissure Ⅱ), the heat transfer is affected by the internal resistance of the overlying strata fracture when the depth of Fissure Ⅱ is greater than10 m, the temperature of Fissure Ⅱ gradually equals to the ground temperature as the fissures’ depth increases, and the fissures are difficult to be identified. The identification effect is most obvious for fissures larger than 16 cm under the same depth. In spring and summer, UAV infrared identification of mining fissures should be carried out during nighttime. This study provides the basis for the optimal time and season for the UAV infrared identification of different types of mining ground fissures.

Investigation of automatic segmentation on digital infrared thermal imaging of breast

Objective: To scan all the possibly diseased areas of an organ, a new method of digital infrared thermal imaging (DITI) system was designed on the basis of medical theory. Methods: This new method of DITT is operated in 2 steps; the image is sharpened with wavelet transformation and then the image is divided into normal and possibly diseased areas with Fuzzy clustering. Results: It was found for a comparison between the old and new methods that the new method is more reliable in clinical practice and takes less time to complete a computation. Conclusion : The new model of DITI system can be used clinically to improve the diagnostic accuracy of breast disease.

Thermal Infrared Salient Human Detection Model Combined with Thermal Features in Airport Terminal

Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.

Calculate Thermal Infrared Intensity of the Hull’s Military Ship

Stealth technology emphasizes on the reduction in reflection and radiation energies, the surface of target's body in the range of visual, radar, thermal and near IR and so on. Providing solutions to reduce thermal IR intensity radiation is one of the appropriate actions in passive defense for identifying power and targeting enemy. Therefore, questions are brought up: How much is the thermal IR intensity radiation of surface of the hall’s vessel? How much is the effect of each parameter? This thesis tries to provide the software to answer these questions. The provided software measures thermal IR intensity radiation of the surface of the hall’s vessel by the material substance, the temperature of the surface of the hall’s vessel, the situation and characteristic of the thermal detector, noticing the coefficient of environment atmospheric transmittal. This software by changing the effective parameters on thermal IR radiation calculates the thermal radiation on thermal detector in different situations.

Gait Recognition System in Thermal Infrared Night Imaging by Using Deep Convolutional Neural Networks

Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.

9μm Cutoff 128×128 AlGaAs/GaAs Quantum Well Infrared Photodetector Focal Plane Arrays

We design and fabricate a 128 × 128 AlGaAs/GaAs quantum well infrared photodetector focal plane array （FPA）. The device is achieved by metal organic chemical vapor deposition and GaAs integrated circuit processing technology. A test structure of the photodetector with a mesa size of 300μm × 300μm is also made in order to obtain the device parameters. The measured dark current density at 77K is 1.5 × 10^-3A/cm^2 with a bias voltage of 2V. The peak of the responsivity spectrum is at 8.4μm,with a cutoff wavelength of 9μm. The blackbody detectivity is shown to be 3.95 × 10^8 （cm · Hz^1/2）/W. The final FPA is flip-chip bonded on a CMOS read-out integrated circuit. The infrared thermal images of some targets at room temperature background are successfully demonstrated at 80K operating temperature with a ratio of dead pixels of less than 1%.

Using shape contexts method for registration of contra lateral breasts in thermal images

AIM: To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. METHODS: The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. RESULTS: In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligningtransformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows:(1) no special land marks or key points are needed;(2) it is tolerant to all common shape deformation; and(3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases.CONCLUSION: We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images.

Applications of Thermal Imaging in Agriculture—A Review

In thermal remote sensing the invisible radiation patterns of objects are converted into visible images and these images are called thermograms or thermal images. Thermal images can be acquired using portable, hand-held or thermal sensors that are coupled with optical systems mounted on an airplane or satellite. This technology is a non-invasive, non-contact and non-destructive technique used to determine thermal properties and features of any object of interest and therefore it can be used in many fields, where heat is generated or lost in space and time. Potential use of thermal remote sensing in agriculture includes nursery and greenhouse monitoring, irrigation scheduling, plants disease detection, estimating fruit yield, evaluating maturity of fruits and bruise detection in fruits and vegetables. This paper reviews the application of thermal imaging in agriculture and its potential use in various agricultural practices.

Development of long-wavelength infrared detector and its space-based application requirements

Infrared detection technology has greatly expanded the ability of mankind to study the earth and the universe. In recent years, the demand for long-wavelength infrared detectors is increasing for their advantages in exploring the earth and the universe. A variety of long-wavelength infrared detectors have been made based on thermal resistive effect, photoelectric effect, etc., in the past few decades. Remarkable achievements have been made in infrared materials, device fabrication,readout circuit, and device package. However, high performance long-wavelength infrared detectors, especially those for large format long-wavelength infrared detector focus plane array, are still unsatisfactory. Low noise, high detectivity, and large format long-wavelength infrared detector is necessary to satisfy space-based application requirements.

Device topological thermal management of β-Ga_(2)O_(3) Schottky barrier diodes

The ultra-wide bandgap semiconductor β gallium oxide(β-Ga_(2) O_(3)) gives promise to low conduction loss and high power for electronic devices. However, due to the natural poor thermal conductivity of β-Ga_(2) O_(3), their power devices suffer from serious self-heating effect. To overcome this problem, we emphasize on the effect of device structure on peak temperature in β-Ga_(2) O_(3) Schottky barrier diodes(SBDs) using TCAD simulation and experiment. The SBD topologies including crystal orientation of β-Ga_(2) O_(3), work function of Schottky metal, anode area, and thickness, were simulated in TCAD, showing that the thickness of β-Ga_(2) O_(3) plays a key role in reducing the peak temperature of diodes. Hence, we fabricated β-Ga_(2) O_(3) SBDs with three different thickness epitaxial layers and five different thickness substrates. The surface temperature of the diodes was measured using an infrared thermal imaging camera. The experimental results are consistent with the simulation results. Thus, our results provide a new thermal management strategy for high power β-Ga_(2) O_(3) diode.

Gradient refractive structured NiCr thin film absorber for pyroelectric infrared detectors

A gradient refractive structured NiCr film that has a high extinction coefficient at far infrared range(8-μm–24 μm) is presented as an absorber for pyroelectric infrared detectors. The absorber features high absorption efficiency due to the low reflection off the structured surface and high absorption across the film thickness. The refractive index and extinction coefficient are extracted using spectroscopic ellipsometry. It is found that the single NiCr film exhibits an increasing refractive index as the gas atmosphere pressure increases, hence the three-layer gradient NiCr absorber can be fabricated by adjusting the gas atmosphere pressure during sputtering deposition. Essential Macleod software has been used to generate an efficient film structure design and the calculations show similar absorptance trend compared to the experimental measurement result. The results indicate that the gradient refractive structured metal thin film absorber can provide high absorption for applications in thermal sensing.

基于红外热成像的围护结构热工性能定量检测方法研究进展

综述红外热成像技术在建筑围护结构热工性能定量检测领域的研究成果,介绍国内外定量红外热成像法的理论基础、发展历程以及在量化热工缺陷能量损失中的应用,从构建稳态热流环境、对流辐射换热计算、测试操作选择3个方面总结现场检测的影响因素,归纳图像处理技术在排除光学干扰、辨识热工缺陷、热工信息可视化等方面对红外检测领域的贡献,分析未来红外热成像的应用前景与发展方向。研究表明,红外热成像技术可成为围护结构热工性能定量检测与热工缺陷量化识别的优秀方法。

基于水传热和红外热成像的煤矸识别方法

基于可见光图像的煤矸识别方法准确率不高、识别速度慢;基于高能射线透射的煤矸识别方法具有很大辐射导致较少应用。红外热成像具有穿透性强、不受光线影响等优点,但煤和矸石的表面温度在室温下相对接近,导致煤和矸石在红外热图像中没有明显差异,难以获得较好的识别效果。针对上述问题,提出了一种基于水传热和红外热成像的煤矸识别方法。在不同水温(18,21,24,27,30℃)条件下进行煤和矸石红外热成像实验,通过煤和矸石红外热图像和温度变化之间的差异来区分煤和矸石。实验结果表明:不同水温下煤和矸石红外热图像不同,当水温低于环境温度时,煤和矸石红外热图像之间的差异较大;在相同水温条件下,煤和矸石红外热图像之间的差异随着时间增加逐渐增大;煤和矸石表面温度变化均随水温升高和时间增加呈增大趋势,但矸石表面温度变化大于煤表面温度变化;当水温为18℃、时间为180 s时,煤和矸石红外热图像之间差异和温差均达到最大。这说明低温的水可作为一种传热介质,更有利于使煤和矸石之间产生较大的温差,从而实现煤和矸石红外热图像准确、快速识别。

500 kV输电线路劣化瓷绝缘子非线性发热特性的红外分析

高压输电线路绝缘子串中的劣化件会威胁电网安全。为了研究劣化瓷绝缘子的红外发热特性,设置了一系列实验,研究了劣化绝缘子的电阻、沿串位置和环境相对湿度对红外检测的影响。并对含有两片劣化绝缘子的绝缘子串进行了附加实验,以研究了正常绝缘子和低值绝缘子之间不同的发热现象。利用有限元分析仿真进一步分析了红外图像中钢帽的发热机理。实验和仿真结果表明:劣化绝缘子的温升与阻值呈非线性关系,当电阻为30 MΩ时温升最大;绝缘子串两端的劣化易被检测;相对湿度过高可能会导致误检;正常绝缘子的发热区域是钢帽的下部,瓷件的温度上升1.2℃左右,而对于劣化绝缘子,沿钢帽的温升分布均匀,瓷件的温度与实验前基本一致。相关研究结果为劣化绝缘子的红外检测提供了参考依据。