摘要
针对传统轮廓检测方法的不足,提出基于全局化边界概率(Gpb)+简单线性迭代聚类(SLIC)相结合的地类边界提取方法,并对不同算法下的检测有效性和稳定性进行了对比分析,结果表明:基于Gpb+SLIC算法的轮廓检测法拥有更高的清晰度、完整性和正确性,且能有效避免冗余轮廓信息的带入,具有较高的地类边界提取效果,可在地籍测绘中予以合理运用。
In view of the shortcomings of traditional contour detection methods,a new method of land class boundary extraction based on the combination of global boundary probability(GPB)+simple linear iterative clustering(SLIC)is proposed,and the effectiveness and stability of detection under different algorithms are compared and analyzed.The results show that:Based on GPB+The contour detection method of SLIC algorithm has a higher definition,integrity and correctness,and can effectively avoid the introduction of redundant contour information.It has a higher effect of land boundary extraction,and can be used reasonably in cadastral mapping.
作者
蒋军娟
JIANG Junjuan(Hangzhou Tongji Surveying and Mapping Company Limited,Hangzhou Zhejiang 311100,China)
出处
《北京测绘》
2020年第12期1763-1766,共4页
Beijing Surveying and Mapping
关键词
轮廓检测
全局化边界概率
简单线性迭代聚
地类边界提取
contour detection
global boundary probability
simple linear iterative clustering
boundary extraction of land class