线扫描铁轨表面缺陷成像与检测

基于线扫描的机器视觉成像系统，用于采集铁轨表面图像，提出一种以图像增强和自动阈值分割为核心的缺陷检测算法，该算法能够准确检测出铁轨表面缺陷.图像增强采用局部零均值法，克服了铁轨表面光线反射不均的缺点，提高了缺陷和背景的区分度.自动阈值分割采用强调概率的最大背景类方差法，取到的阈值使背景类方差最大的同时保持缺陷出现概率较小.将本文的核心方法与传统方法进行对比实验，验证了该算法的有效性和快速性，具有一定的实用价值.

Imaging and Detection of Rail Surface Defects Based on Line Scanning

This paper introduced a machine vision imaging system to acquire rail surface images based on line scanning, and presented an algorithm to detect rail surface defects accurately based on image enhancement and automatic thresholding. We proposed a local zero mean measure to enhance rail images, which can overcome the nonuniform reflection of the rail surface and improve the distinction between defects and background. And then, we put forward a proportion emphasizing maximum background-class variance measure to select a threshold, which maximizes the background-class variance and meanwhile keeps the defect proportion in a low level. Through experiments, we compared the core of the algorithm with well-established methods, and then proved the validity and rapidity of the algorithm with wide applicability.