DEB: definite error bounded tangent estimator for digital curves.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society(2014)

引用 17|浏览18
暂无评分
摘要
We propose a simple and fast method for tangent estimation of digital curves. This geometric-based method uses a small local region for tangent estimation and has a definite upper bound error for continuous as well as digital conics, i.e., circles, ellipses, parabolas, and hyperbolas. Explicit expressions of the upper bounds for continuous and digitized curves are derived, which can also be applied to nonconic curves. Our approach is benchmarked against 72 contemporary tangent estimation methods and demonstrates good performance for conic, nonconic, and noisy curves. In addition, we demonstrate a good multigrid and isotropic performance and low computational complexity of O(1) and better performance than most methods in terms of maximum and average errors in tangent computation for a large variety of digital curves.
更多
查看译文
关键词
deb,definite error bounded tangent estimator,image processing,nonconic curves,noisy curves,digital curves,isotropic performance,computational complexity,digitization,computer vision,multigrid performance,geometric-based method,digital conics,tangent estimation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要