摘要
在分析输电线路无人机巡检系统航拍图像中绝缘子及其自爆缺陷特征的基础上,提出一种玻璃绝缘子自爆缺陷的检测及定位方法。该方法首先在色调、色饱和度、亮度(HSI)颜色空间分别对H(Hue)和S(Saturation)分量运用最大类间方差法(OTSU)分割图像,获取绝缘子前景连通域;之后,运用直方图方法对检测到的前景轮廓的倾角和面积分布进行统计,准确识别绝缘子轮廓;最后,设计了一种特征检测算法,检测并标记自爆绝缘子位置。实验证明该方法能从自然背景中准确检测并定位绝缘子自爆缺陷,具有较好的工程应用价值。
By analyzing the characteristics of the glass insulator and its defects in aerial images of the unmanned aerial vehicle inspection system, a method is presented to extract glass insulator and detect defects. The OTSU＇s thresholding method is applied to H and S components in Hue,Saturation,Intensity （HSI） color space for image segmentation; and then, the distribution of the contours＇ angle and area is calculated by using the histogram method to obtain the position of glass insulators accurately. Feature detection algorithm is proposed to detect the glass insulators and mark out the defects. Experimental results indicate that the method can mark the location of the defects accurately in the aerial images with natural background, which has a i good practical value.
出处
《太赫兹科学与电子信息学报》
2013年第4期609-613,共5页
Journal of Terahertz Science and Electronic Information Technology
基金
高等学校博士学科点专项科研基金资助项目(20113218110013)
关键词
航拍图像
绝缘子识别
缺陷检测
最大类间方差(大津)法
aerial image
insulators extraction
detect defects
maximal variance between clusters（OTUS） method
