摘要
为解决基于积水可见光图片处理时,受光照变化影响大、夜晚及恶劣天气下难以成像,或成像图像质量低到无法识别的问题.提出一种利用红外热成像+图像处理技术进行积水区域识别的方法,利用红外成像技术拍摄道面积水图像克服了传统拍照方式受光照条件限制的缺陷,进一步针对红外成像积水边界边缘模糊、边缘温度分布无明显规律的特征,提出基于Canny算子和模糊C均值聚类的红外图像积水边缘检测融合算法,并利用该算法对实拍积水红外图像进行处理分析,结果表明:该算法对模糊边界有良好的提取效果,图像分割结果与人工标注的实际面积误差在7％以内,且利用像素点的比值能够快速、准确地获取积水面积,为湿滑跑道道面状况评估提供量化支撑,为飞机在湿滑道面上的安全运行提供有效技术支撑.
Abstract
To address the problem that water color image processing result is greatly affected by illumination changes,especially in bad weather.Based on infrared image a method of identifying water accumulation area was proposed,which overcame the limitation of color image processing method by illumination conditions.Further,a fusion algorithm for detecting the edges of infrared image water accumulation based on the Canny operator and fuzzy C-means clustering was proposed to solve the blurred edges and lack of clear temperature distribution laws in infrared imaging water accumulation.The results show that the algorithm achieves a good extraction effect on the fuzzy boundary,and the error between the image segmentation result and the actual area marked by manual is less than 7％.The ratio of pixels can quickly and accurately obtain the water accumulation area,which provides quantitative support for the evaluation of the wet runway surface condition and provides effective technical support for the safe operation of the aircraft on the wet runway surface.
维普
万方数据