基于突变信号检测的光学标记识别图像分割方法

OMR image segmentation based on mutation signal detection

针对无定位信息的光学标记识别(OMR)图像填涂区的精确定位问题,提出了一种基于小波变换突变信号检测的图像分割方法。该算法首先计算图像的水平和垂直投影函数,然后投影函数经过迭代小波变换后检测其突变点,突变点能够精确地反映OMR信息的边界位置。检测算法的适应性基于有限次数的小波变换和突变信号检测过程。实验结果表明该算法具有较高的分割精度和稳定性,分割精度均方差可以达到0.4167个像素。而且由于算法只使用图像的水平和垂直投影信息,因此具有较高的执行效率;投影函数的统计特性和小波变换的多分辨特性则使得该分割算法对噪声不敏感。

Concerning the accurate positioning of Optical Mark Recognition（OMR） images without any position information,an image segmentation approach of mutation signal detection based on wavelet transformation was proposed.Firstly,the horizontal and vertical projective operations were processed,and then these functions were transformed by wavelet to detect mutation points,which can better reflect the boundary of OMR information.This algorithm＇s adaptability is based on limited times of wavelet transform and mutation signal detection.The experimental results demonstrate that the method possesses high accuracy of segmentation and stability,and the mean square error of segmentation accuracy can be 0.416 7 pixels.The processing of this method is efficient because the segmentation only used the horizontal and vertical information.This algorithm is not sensitive to noise because of the statistic characteristic of projection functions and multi-resolution characteristic of wavelet tranformation.