Design of steerable filters for feature detection using Canny-like criteria
Design of steerable filters for feature detection using Canny-like criteria
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DOI：
10.1109/tpami.2004.44
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发表时间：
2004-08-01
影响因子：
23.6
通讯作者：
Unser, M
中科院分区：
文献类型：
--
作者：
Jacob, M;Unser, M
我们提出了一种基于类canny准则优化的二维特征检测器设计的通用方法。与以前的计算设计相比，我们的方法是真正的2D，并提供具有封闭形式表达式的过滤器。它还产生了比经典梯度或基于hessian的探测器具有更好取向选择性的算子。我们通过设计边缘和脊检测算子来说明该方法。我们给出了一些实验结果，证明了这些新的特征检测器的性能改进。我们提出了计算效率高的局部优化算法来估计特征方向。我们还引入了形状自适应特征检测的概念，并将其用于图像角点的检测。
We propose a general approach for the design of 2D feature detectors from a class of steerable functions based on the optimization of a Canny-like criterion. In contrast with previous computational designs, our approach is truly 2D and provides filters that have closed-form expressions. It also yields operators that have a better orientation selectivity than the classical gradient or Hessian-based detectors. We illustrate the method with the design of operators for edge and ridge detection. We present some experimental results that demonstrate the performance improvement of these new feature detectors. We propose computationally efficient local optimization algorithms for the estimation of feature orientation. We also introduce the notion of shape-adaptable feature detection and use it for the detection of image corners.