Robust Corner Detection Based on Multi-scale Curvature Product in B-spline Scale Space
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摘要: 本文在B样条尺度框架下提出了一种多尺度曲率乘积角点检测算法. 根据在各个尺度下的轮廓的曲率, 建立了尺度积函数. 在各个尺度下的曲率乘积经阈值变换后的局部极大值定义为角点. 通过尺度积, 根据CNN评价标准, 角点的定位精度和检测性能得到显著的提高. 实验也证明本文算法对边缘细节具有很好的鲁棒性并获得了良好的检测结果.Abstract: This paper presents a multi-scale curvature product corner detection technique in the framework of B-spline curvature scale space. A scale product function is derived from the curvature product of the contour at different scales. Corners are constructed as the local maxima by thresholding the curvature product results across several scales. Through scale product, the localization accuracy and detection performance can be notably improved in terms of CNN criteria. Experiments also demonstrate that proposed method shows robustness to high frequency details and provides promising detection results.
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