摘要
边界检测一直是图象分析处理的重点和难点。现在的边界检测算法(如K-L变换、Sobel算子的梯度检测、模板检测等)在不同程度上存在着抗噪声能力不强、算法计算量过大的缺点,不适于实时应用。新出现的一批智能化自适应算法(如Tabu搜索算法、遗传算法等)在此方面有很大改进。本文主要介绍Tabu算法在边界检测中的运用。
Edge finding has been a difficult and important task in image processing. The current edge-finding algorithms (e.g. K-L transformation, Sobel gratitude edge finding, model matching) are vulnerable to noise or need too much computation, which are not suitable for real-time applications. Recently-emerged intelligent adaptive algorithms , such as the Tabu algorithm and GAs, have improved a lot. This paper will mainly introduce the application of the Tabu algorithm in edge finding.
出处
《计算机工程与科学》
CSCD
2003年第2期1-2,19,共3页
Computer Engineering & Science
