Fusion Reconstruction Method for 3D Temperature Fields on the Human Body Surface
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摘要: 重建人体体表三维温度场能够为包括诊断在内的多项人体医学分析提供可靠数据。由于红外成像具有温度测量精度低、成像分辨率不足以及显示效果较差等缺陷，导致重建的目标三维温度场的可靠性存在不足。针对这些问题，提出一种针对人体体表的三维温度场的融合重建方法。即首先采用黑体测温标定的方法，对红外热像仪的测温结果进行误差修正；其次对红外图像进行对比度增强处理；之后进行超分辨率处理，使红外图像在空间分辨率上匹配三维数据；最后在数据融合阶段，基于不同图像中提取到的靶标特征点对应空间中相同位置的事实，对标定得到的系统结构参数进行误差修正。实验表明，该方法使三维温度场的测温精度达到0.26℃以下，温度场的三维分布结果得到提升，显示效果也得到了增强。Abstract: Reconstruction of 3D temperature fields on the human body surface can provide reliable data for a number of human medical analyses, including diagnoses. Based on the limitations of infrared imaging, such as poor temperature measurement accuracy, insufficient imaging resolution, and poor display effects, the reliability of the 3D temperature field collected using infrared imaging is low. To overcome these problems, we propose a fusion reconstruction method for 3D temperature fields on the human body surface. First, the blackbody temperature measurement and calibration method is used to correct the errors in the temperature measurement results of an infrared thermal imager. Second, contrast enhancement processing is applied. Third, super-resolution processing is used to make the infrared images match the 3D data in terms of spatial resolution. Finally, in the data fusion stage, based on the fact that the target feature points extracted from different images correspond to the same position in the space, the system structure parameters obtained through calibration are corrected. Experimental results demonstrate that the temperature error of the 3D temperature field is less than 0.26℃, the 3D distribution of the temperature field is improved, and the display effect is enhanced.
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图 4 热像仪测温标定曲线
Figure 4. Thermal imaging camera temperature measurement calibration curve
图 7 红外图像及直方图增强前后结果：增强前（左），增强
Figure 7. The results before and after the infrared image and histogram enhancement: Before (left), after (right)
图 9 红外图像预处理前（左）后（右）的三维温度场重建
Figure 9. Reconstruction results of 3D temperature field before(left) and after(right) infrared image preprocessing
图 11 修正前后的靶标三维温度场与空间分布曲线
Figure 11. Target 3D temperature field and spatial distribution curves before and after correction
图 12 人体体表部分区域的三维温度场融合模型结果
Figure 12. Results of 3D temp. field fusion model in parts of the human body surface
表 1 手背部分区域测温修正结果
Table 1. Temperature measurement correction results of the hand back
Area T/℃ T0/℃ Tt/℃ E0/℃ Et/℃ Advance 1 36.28 35.11 36.35 1.17 −0.17 85.47% 2 36.71 36.20 36.61 0.51 0.10 80.39% 3 35.45 34.03 35.20 1.42 0.25 82.39% 4 36.10 35.27 36.22 0.83 −0.12 85.54% 5 35.69 34.54 35.87 1.15 −0.18 84.34% 
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表 2 人脸三维温度场融合重建结果分析
Table 2. Analysis on 3D temp. fusion reconstruction of human face
Region D0/mm D/mm ED/mm T0/℃ T/℃ ET/℃ Left eye 27.005 26.8 0.205 36.10 35.91 0.19 Right eye 23.907 24.1 -0.193 35.81 35.55 0.26 Nose 37.553 37.8 -0.247 36.03 36.15 0.12 Mouth 34.211 34.3 -0.089 36.22 36.09 0.13
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