基于OTSU的近红外图像分割的应用研究

Application Research of the Segmentation of Near-Infrared Image Based on OTSU

OTSU法是最常用的利用图像的一维灰度直方图的阈值化方法之一,二维OTSU除了考虑像素点的灰度信息外还考虑了像素点与其邻域的空间信息。由于红外图像不同于一般灰度图像的一些特征,有针对性的采用了二维OTSU对其进行分割。通过与一维OTSU的相互比较可以看出,二维OTSU对近红外图像拥有更好的分割效果,能有效的分割出炉管图像,对后期的温度监测和声光报警具有重要的意义,提高了高温炉的安全性。

OTSU is one of the most commonly used image-threshold methods,which based on one-dimension histogram of image＇s gray level.The two-dimension OTSU takes the gray level of pixel point,as well as the spatial information between the pixel point and its field into consideration.Because of infrared image, different from the general characteristics of gray image,the two-dimensional OTSU segmentation is targeted adopted.According to the comparison with one-dimension OTSU,it is indicated that the two-dimension OTSU can segment the near-infrared image better and get the furnace image more effectively.By monitoring its temperature in the late period and alarming through sound and light,it greatly enhances the security of high- heat furnace.