基于二维直方图的曲线分割法  

Curve Segmentation Algorithm Based on Two-Dimensional Histogram

作　　者：张书真[1] 向晓燕[1] 赵英男[2] 宋海龙[3] 

机构地区：[1]吉首大学物理科学与信息工程学院,湖南吉首416000 [2]南京信息工程大学计算机与软件学院,江苏南京210044 [3]吉首大学信息管理与工程学院,湖南张家界427000

出　　处：《微电子学与计算机》2010年第9期20-23,28,共5页Microelectronics & Computer

基　　金：国家自然科学基金项目(60573028);湖南省教育厅自然科学基金项目(07C526)

摘　　要：针对传统十字分割模型对于二维直方图的划分不合理,提出一种曲线分割模型,并通过多条线段拟合简化该模型.在分割阈值的求解过程中,将二维阈值转换为一维阈值,且为获得快速算法,采用了迭代和优化搜索策略.实验表明,曲线分割模型比十字分割模型具有更优的抗噪性能,对于图像边缘形状保持得好,并且此算法的运算量大大降低.A curve segrnetation model is presented, which overcomes the unreasonable division of two-dimensional histogram based on the traditional cross segmentation model. The simplified model is also get by multi-line fitting. In the process of solving the threshhold, the Mgorithn transfer the two-dimentional threshold to one-dimentional threshold. And in order to get the fast calculation, an iterative method and an optimizing search strategy is used. Compared with the cross segmetation model, the curve segmentation model has the better performance of anti-noise. It maintains the better shape of image edge, and the computation of algorithm is greatly reduced.

关 键 词：曲线分割模型 十字分割模型 拟合 阈值 迭代 优化搜索 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]