基于自适应投影分割的接触网号牌字符提取

Segmentation of catenary plate characters based on the adaptive projection method

针对接触网故障巡检,传统的人工巡检方式效率低下,不能及时发现潜在安全隐患。基于此,针对接触网的智能视频巡检,成为目前研究的重点。对接触网图像的智能分析,首先要实现对接触网杆的定位识别,而对接触网号牌字符进行精确提取,是实现接触网号牌识别的前提。由于背景干扰,传统的Hough矩形检测识别率较差,现提出了一种基于几何特征检测及自适应投影分割的接触网号牌字符提取方法:首先对号牌的矩形结构进行拆分检测,分别对不同方向的线条进行检测,求取不同方向的边框宽度及坐标,得到精细号牌区域,再采用自适应投影分割方法对单个字符进行提取。实验证明,该方法的字符提取正确率在92%以上,验证了该方法的有效性。

In view of the catenary fault inspection,the traditional manual inspection is inefficient,can＇t found security hidden danger in time,and can ＇t meet the requirements. Based on this,catenary of intelligent video inspection,became the focus of the research at present. Intelligent analysis of catenary images,positioning of catenary pole number recognition is the first step. Due to the background interference,the traditional Hough rectangular test has poor recognition rate. This paper proposes a catenary plate character extraction method, based on geometric feature detection and the adaptive projection method. It splits the plate rectangular structure,detecting horizontal and vertical lines to get the accurate plate area. Then it uses adaptive projection method to extract characters. The experiment proved that,the accuracy of this method is above 92%,it is the effectiveness of the proposed method.