基于前景提取与多特征决策融合的电力线触树放电痕迹识别OACSTPCD

During the intelligent inspection of power lines,it is difficult to accurately identify the traces caused by power lines touching trees,and cannot provide a reliable basis for accident prevention and responsibility division.To solve these problems,the power line dis-charge trace identification method based on foreground area extraction and multi-feature decision fusion is proposed.Firstly,the experi-ment platform of contact tree discharge of medium voltage line is built,and the surface discharge trace is collected and the image set is constructed.Then,a de-shading algorithm combining texture sparsity and logarithmic transformation is proposed to eliminate the inter-ference of shadow region.Furthermore,a target initial frame selection strategy combining global threshold and adaptive threshold seg-mentation is proposed,to address the problem that initial frame cannot be determined automatically in GrabCut algorithm.It realizes automatic and accurate segmentation of line trace under complex backgrounds.Finally,the texture and color features are extracted,and the power line trace recognition is realized by multi-SVM decision fusion.The experimental results show an average recognition accuracy of 88.39％,proving the effectiveness of the proposed method.