在基于CCD图像传感器的非接触高温温度场软测量中，为了计算高温图像目标的温度，必须先从辐射图像中准确识别待测目标。由于工业现场采集的高温熔体图像中存在多种噪声，导致图像目标难以准确识别。提出一种目标图像分类识别方法，即先利用多光谱图像分割方法来减少甚至消除各种高温噪声；然后运用改进的最大类间方差法进一步分割以去除烟雾干扰；最后运用数学形态学方法消除分割图像中的游离点和孔洞，使目标边缘光滑。实验结果表明，该方法能够从多种干扰图像中准确识别出高温辐射体图像目标，有较强的实用性。

In order to measure the temperature of radiation image target，the measured target must be recognized accurately from radiation images in the non-contact soft measurements of temperature field based on CCD image sensor. It is difficult to recognize the image target because of the existence of various interferences in radiation images captured in industrial locale. A classification recognition method is proposed. By multi-spectrum segmenting，various high-temperature noises in the radiation color image are reduced or even eliminated. And then with the improved Ostu segmentation algorithm，the interference of smog is eliminated. Finally，the morphology method in mathematics is applied to process the segmented image and remove the dissociations and narrow holes to smooth the image’s edge. The experimental results show that the method can recognize high-temperature melt target from high-temperature radiation image with various interferences accurately and it has an excellent practicability.