钢绳芯胶带图像缺陷特征自动提取技术

结合磁检测和X射线检测技术，实现钢绳芯胶带的事故隐患检测，以确保胶带输送机的安全使用。实现胶带射线图像中缺陷特征的自动提取，是保障整个检测系统实时性的关键。重点以接头抽动特征的提取为例，提出一种胶带射线图像中缺陷特征自动提取的方法。算法对存在缺陷的胶带射线图像进行降噪和剪裁处理，以减少无用信息；基于图像水平方向灰度差分的方法弱化钢丝绳信号对缺陷信息的干扰；对图像实施二值化分割，并利用图像中连通的亮点区域的面积来区分缺陷目标和噪声，以提取缺陷区域信息；通过图像扫描得到缺陷的位置和尺寸信息。实验结果证明了算法的可行性。

Auto Defect Extraction of Steel-Cord Conveyor Belt

A detection system based on hybrid of magnetic method and radiography imaging technique is adopted to detect the hidden causes of accidents and ensure the safe operation of steel-cord conveyor belt. It is necessary to implement auto defect extraction of X-ray image of steel-cord conveyor belt for the real-time performance of the whole detection system. This paper lays special stress on studying the auto defect extraction method taking connector stretch for instance. The malfunction images of steel-cord belts are denoised and trimed firstly to decrease useless data. Then the interference from steel-cord is reduced using horizontal gray differential method. Image binarization based on histogram as well as denoise algorithm based on area of continuous bright pixels are implemented to obtain the pure defect signal. Finally the position and size informations of defect are extracted. The experimental results evaluate the effectiveness of the algorithm.