基于灰度突变的扣件区域定位方法研究

钢轨扣件定位方法对图像质量和定位精度都有很高的要求,为此,提出了一种基于灰度突变的钢轨扣件定位方法。首先,通过改进的中值滤波器对图像去噪。然后,根据图像频域特点对图像进行小波分解,提取低频分量,并对低频分量进行滤波和伽马变换处理以减少自然环境因素对图像质量的影响。接着,根据图像中不同区域灰度值的变化规律统计分析图像列和行方向灰度突变情况,从而定位出钢轨轨面和轨枕区域。最后,利用轨面、轨枕和扣件三者在图像中的位置关系对扣件区域进行准确定位。实验结果表明,该方法的定位准确率达93.19%,能快速有效地定位出扣件区域,且具有较强的环境适应性、鲁棒性和实用性。

Fastener region location method based on gray-scale mutation

Rail fastener positioning method has high requirements for image quality and positioning accuracy.Therefore,a rail fastener positioning method based on gray mutation is proposed.Firstly,the image is denoised by an improved median filter. Then,according to the characteristics of image frequency domain,the image is decomposed by wavelet transfrom to extract low-frequency component,and the low-frequency component is filtered and processed by gamma transformation to reduce the influence of natural environment factors on image quality.After that,according to the change rule of gray-scale values of different regions in the image,the gray-scale mutation in column and line directions of the image is statistically analyzed,and then the rail surface and the sleeper are located.Finally,the fastener area is accurately located by using the position relationship of the rail surface,the sleeper and the fastener in the image.The experimental results show that the positioning accuracy of the proposed method is 93.19 ％,which can quickly and effectively locate the fastener region,and has strong environmental adaptability,robustness and practicability.