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SCENE COMPLEXITY ANALYSIS USING RANDOM CURVES

机译:使用随机曲线的场景复杂度分析

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We present a novel method for the analysis of scene complexity based on integral geometry. We use random families of ellipses and measure the number of intersections between these curves and the objects in images. The intersection number gives a good measure of the scene complexity - the higher the complexity of the image the higher would be the intersection number. The proposed method is applicable to arbitrary scenes and to any types of grids for digitization. Our method improves an earlier work in which random lines were used to estimate scene complexity. For objects that are not of square shapes, a random family of ellipses is found to be better than a random family of lines in measuring the scene complexity. The numbers of intersections correlate to the density of the curves. Also, the orientation of the family of ellipses influences the number of intersections to some degree. Experimental results are given to illustrate the proposed method.
机译:我们提出了一种基于积分几何分析场景复杂度的新方法。我们使用椭圆的随机族,并测量这些曲线与图像中的对象之间的相交数。交叉点编号可以很好地衡量场景的复杂性-图像的复杂度越高,交叉点编号就越高。所提出的方法适用于任意场景和任何类型的数字化网格。我们的方法改进了早期的工作,其中使用随机线来估计场景复杂度。对于非正方形的对象,在测量场景复杂度时,发现椭圆形的随机族比线形的随机族更好。相交的数量与曲线的密度相关。同样,椭圆族的方向在一定程度上影响交叉点的数量。实验结果表明了该方法的有效性。

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