文章基本信息

标题：A Novel Histogram Region Merging Based Multithreshold Segmentation Algorithm for MR Brain Images
本地全文：下载
作者：Siyan Liu ; Xuanjing Shen ; Yuncong Feng 等
期刊名称：International Journal of Biomedical Imaging
印刷版ISSN：1687-4188
电子版ISSN：1687-4196
出版年度：2017
卷号：2017
DOI：10.1155/2017/9759414
出版社：Hindawi Publishing Corporation
摘要：Multithreshold segmentation algorithm is time-consuming, and the time complexity will increase exponentially with the increase of thresholds. In order to reduce the time complexity, a novel multithreshold segmentation algorithm is proposed in this paper. First, all gray levels are used as thresholds, so the histogram of the original image is divided into 256 small regions, and each region corresponds to one gray level. Then, two adjacent regions are merged in each iteration by a new designed scheme, and a threshold is removed each time. To improve the accuracy of the merger operation, variance and probability are used as energy. No matter how many the thresholds are, the time complexity of the algorithm is stable at . Finally, the experiment is conducted on many MR brain images to verify the performance of the proposed algorithm. Experiment results show that our method can reduce the running time effectively and obtain segmentation results with high accuracy.