Improved Image Preprocessing Algorithm for Rail Surface Defects Detection

It is a challenge to detect discrete defects in a vision system because of illumination inequality and low contrast of rail images which obtained by linear array camera.This paper presents a local nonlinear contrast（LNC）enhancement and an improved maximum entropy（IME）threshold segmentation to preprocess images.LNC enhances the contrast by mapping relatively low gray level to lower gray level,high gray level to higher gray level.By analyzing curves of objects entropy,background entropy and gray-level probability distribution of image,we proposed IME algorithm to segment the image which selects a threshold that maximizes the object entropy and meanwhile keeps the object proportion in a low level,therefore,the pre-processed images contain less noise.The experimental results demonstrate that the LNC algorithm is easy to implement and enhances the image fast and effectively.What’s more,it is illumination independent.IME segments image with smaller threshold and less noise compared with maximum entropy,object entropy and OSTU threshold segmentation methods.The undetected rate and false detection rate of improved preprocessing algorithms for test images is 6.2%and 7.3%,respectively.