An Binarization Method by Background Estimation Based on Double Moving Average
An improved binarization method based on moving average method to estimate background illumination is proposed for threshold segmentation problem of images with uneven illumination.First,the quadratic moving average prediction method is used to predict the trend of the grayscale sequence in the one-dimensional image space.Then the boundary point between the fore-ground and the background is found according to the predicted trend to estimate the background,and the background difference method is used to separate the target foreground image.Finally,the maximum inter-class variance method is used to perform global segmentation to obtain segmentation results.To verify the effectiveness of the algorithm,50 images under non-uniform lighting con-ditions are used as test samples in the experiment,and compared with several local threshold segmentation algorithms.Compared with the traditional threshold segmentation algorithm,experimental results show that the algorithm has better performance in reduc-ing the impaction caused by non-uniform illumination and enhance the quality of images.At the same time,it also has a significant improvement in processing speed.
国家科技期刊平台
NSTL
万方数据
