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Characterization of keypoints in images

机译:图像中的关键点的特征

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In this contribution we investigate the performance of steerable functions to characterize keypoints. Steerable functions were introduced recently by Perona as an efficient method to calculate the response of a filter in a continuum of orientations, scales, and other parameters. For the analysis of points with events at multiple orientations, functions with a high orientational resolution are needed. We discuss criteria to judge the quality of a function to serve for orientation analysis. To handle line as well as edge junctions, we use a complex function with the real and imaginary part approximately in quadrature. An associated one- sided function allows to distinguish between terminating and nonterminating edges and lines. To analyze thick lines and blurred edges the function is also steered in scale.
机译:在这一贡献中,我们调查可操纵函数来表征关键点的性能。最近通过PERONA作为一种有效的方法来计算可控功能,以计算滤波器在取向,尺度和其他参数的连续范围内的滤波器的响应。为了分析具有多种方向事件的点,需要具有高定位分辨率的功能。我们讨论标准以判断函数的质量以用于定向分析。要处理线路以及边缘连接,我们使用具有真实和虚部的复杂功能大致在正交中。相关的单面函数允许区分终止和不确定边缘和线路。分析粗线并模糊边缘,功能也以规模引导。

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