Curve segmentation by continuous smoothing at multiple scales

C. Orrite-Uruñuela, J. E. López, A. Alcolea
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引用次数: 6

Abstract

In the case of curve description, the accurate and precise estimation of corners plays an important role. Corners exhibit a high change of curvature /spl kappa/', so we propose the location of them by means of the estimation of /spl kappa/' at different scales of smoothing. The main problem arises when the curvature is computed because of the inherent quantization. We propose to calculate the curvature of contours detected at subpixel level so that, the quantization error is reduced. Once the change of curvature has been estimated, the curve is segmented at high /spl kappa/' points. It is important to emphasise the fact that the curves are segmented before a smoothing at coarser scale is applied, otherwise two close corners could be merged as smoothing increases.
多尺度连续平滑曲线分割
在曲线描述中,角点的精确估计起着至关重要的作用。角点曲率/spl kappa/'变化较大,因此我们提出了在不同平滑尺度下,通过估算/spl kappa/'来确定角点的位置。由于固有的量化,在计算曲率时出现了主要问题。为了减小量化误差,我们提出在亚像素水平上计算轮廓的曲率。一旦估算出曲率的变化,曲线在高/spl kappa/'点处被分割。重要的是要强调这样一个事实,即在应用较粗尺度的平滑之前对曲线进行分割,否则随着平滑的增加,两个接近的角可能会合并。
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