基于改进的两维Otsu管道红外图像高温区域分割研究

石化管道通常可分为常温区域和高温区域两部分。高温区域的存在影响着整个系统的安全运行，热量的散失将会引起资源的浪费及环境的污染等一系列问题。红外光谱图像能够较好地描述石化管道的高温区域，但是如何从中提取高温区域是红外光谱图像处理的一类难题。为实现从红外图像中，将高温区域准确快速分割出来的目的，基于经典的一维Otsu算法提出一种改进的二维多阈值自动获取方法。该算法首先对管道红外图像进行经典单阈值分割，将图像划分为背景和管道两部分。然后基于管道图像区域，以管道灰度图像与平均值图像作为图像二维,对目标图像进行二维双阈值分割，最终将较大的阈值作为划分管道常温区域与高温区域的分割点。将本算法对不同的管线进行多次试验分析，结果表明，采用改进的二维Otsu多阈值算法能够更加清晰的将管道从复杂背景中提取出来，并在此基础上把高温区域更精确的分割。

Research on High Temperature Region Segmentation of Infrared Pipeline Image Based on Improved Two-Dimensional-Otsu

The petrochemical pipeline can usually be divided into the normal temperature region and the high temperature region. The existence of high temperature region affects the safe operation of the whole system, and the loss of heat will cause a series of problems, such as the waste of resources and the pollution of the environment. For the realization of quickly and accurately separating the high temperature region from the infrared image, based on the basic one-dimensional Otsu algorithm we propose an improved two-dimensional multi threshold method. First, the algorithm divides the infrared image of pipeline into two parts: background and pipeline through classical single threshold segmentation. Then, based on the image region of the pipeline, the two thresholds of the target image are divided by the two dimensional image of the pipeline gray image and the average value image, and the larger threshold is finally taken as the segmentation point of the normal temperature region and the high temperature region. We analyze the different pipeline for several tests. The results show that the improved two-dimensional Otsu threshold algorithm can extract the pipeline from complex background more clearly, and on the basis of the step segment the high temperature region more accurately.