【作者】 张明； 张仁斌； 高森； 李晓林；

【Author】 Zhang Ming Zhang Renbin Gao Sen Li Xiaolin (Hefei University Of Technology Hefei 230009)

【机构】 合肥工业大学；

【摘要】 红外成像技术已广泛应用于故障监测领域。对电力设备红外图像分割是对其进一步处理的基础。由于红外图像的特点,传统的方法不能获得较好的分割效果。为此提出了一种基于马尔可夫随机场(Markov Random Field,MRF)模型的电力设备红外图像分割算法。该算法首先采样获取初始参数,使用K均值算法对红外图像初始分割,最后使用ICM算法获取MAF,准则的分割结果。该算法应用于实际变电站红外图像分割中取得较好的效果。更多还原

【Abstract】 Infrared imaging technology has been widely used in the field of fault detection.The segmentation of power equipment infrared image is the foundation of further analysis processing.Because of the characteristics of the infrared images,the traditional method cannot obtain better segmentation results.This paper proposes a segmentation algorithm of power equipment infrared image based on Markov Random Field(MRF).The algorithm first uses sampling method to get initial parameters,then uses K-means algorithm to obtain the initial segmentation of infrared images,finally uses ICM algorithm to get segmentation results of MAP criteria.The algorithm is used in the actual substation infrared images and has obtained satisfied results.更多还原