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A new algorithm for detecting corners in digital images

机译:一种检测数字图像角点的新算法

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Corners and vertices are important features in images, which are frequently used for scene analysis, stereo matching and object tracking. Many algorithms for detecting the corners have been reported up to now. In this paper, a new algorithm is presented. The algorithm is based on measuring the variance of the directions of the gradient of brightness. The probability of the event that a point belongs to the approximation of a straight segment of the isoline of brightness passing through the point being tested is computed using the technique of Bayesian estimations and used as a weight. The algorithm is presented both from the theoretical and from the practical point of view. The results of tests show that the algorithm is better than other known algorithms that are usually used for solving the problem.
机译:角和顶点是图像中的重要特征,通常用于场景分析,立体匹配和对象跟踪。迄今为止,已经报道了许多用于检测拐角的算法。本文提出了一种新的算法。该算法基于测量亮度梯度方向的方差。使用贝叶斯估计技术计算出一个点属于通过测试点的亮度等值线的直线段的近似值的事件的概率,并将其用作权重。从理论和实践的角度介绍了该算法。测试结果表明,该算法优于通常用于解决问题的其他已知算法。

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