SCALE-BASED DETECTION OF CORNERS OF PLANAR CURVES
SCALE-BASED DETECTION OF CORNERS OF PLANAR CURVES
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DOI：
10.1109/34.126805
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发表时间：
1992-04-01
影响因子：
23.6
通讯作者：
CHIN, RT
中科院分区：
文献类型：
--
作者：
RATTARANGSI, A;CHIN, RT
提出了一种平面曲线角点的检测与定位方法。该技术是基于高斯尺度空间，其中包括在所有尺度的边界函数的绝对曲率的最大值。首先分析了孤立单角点和双角点的尺度空间，研究了由于光滑和相邻两个角点之间的相互作用而导致的尺度空间行为。分析表明，生成的比例空间包含的线型图案要么持续存在，要么终止，要么与相邻的线合并。接下来，尺度空间被转换成一棵树，它提供了多个尺度下角点的简单而简洁的表示。最后，一个多尺度角点检测计划的开发使用粗到细的树解析技术。解析方案是基于一个稳定的标准，指出一个角落的存在，必须符合曲率最大可观察到在大多数尺度。实验结果表明，尺度空间角点检测器是可靠的多尺寸功能和噪声边界的对象，并与其他角点检测器进行了测试。
A technique for detecting and localizing corners of planar curves is proposed. The technique is based on Gaussian scale space, which consists of the maxima of absolute curvature of the boundary function presented at all scales. The scale space of isolated simple and double corners is first analyzed to investigate the behavior of scale space due to smoothing and interactions between two adjacent corners. The analysis shows that the resulting scale space contains line patterns that either persist, terminate, or merge with a neighboring line. Next, the scale space is transformed into a tree that provides simple but concise representation of corners at multiple scales. Finally, a multiple-scale corner detection scheme is developed using a coarse-to-fine tree parsing technique. The parsing scheme is based on a stability criterion that states that the presence of a corner must concur with a curvature maximum observable at a majority of scales. Experiments were performed to show that the scale space corner detector is reliable for objects with multiple-size features and noisy boundaries and compares favorably with other corner detectors tested.