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An improved Harris corner detection algorithm for low contrast image

机译:一种改进的用于低对比度图像的Harris角点检测算法

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In seas security supervision, we should conduct feature extraction and match for consecutive frames in order to effectively reduce the jitter caused by wind-induced vibration. Harris corner point detection algorithm is widely used in feature extraction for images. An improved algorithm for Harris corner detection is proposed in this paper since the feature points of images with large size, high pixel and low contrast ratio can not be extracted accurately, especially for seas security monitoring. To begin with, comparing with the eight pixel points around, we can select some possible corner points. And then, by curve fitting, we can choose the pixel points whose R values reach the maximum values in the X and Y directions as the another kind of possible corner points. On top of this, the above two kinds of possible conner points are processed by Susan operator so as to take out the peripheral points and pseudo points, and the best match points can be obtained. The experimental results on seas security applications show the effectiveness and feasibility of the proposed method.
机译:在海上安全监督中,应进行特征提取和连续帧匹配,以有效减少风振引起的抖动。哈里斯角点检测算法被广泛用于图像特征提取中。针对大尺寸,高像素,低对比度的图像特征点无法准确提取的问题,提出了一种改进的哈里斯角点检测算法,特别是在海洋安全监控中。首先,与周围的八个像素点进行比较,我们可以选择一些可能的角点。然后,通过曲线拟合,我们可以选择R值在X和Y方向上达到最大值的像素点作为另一种可能的拐角点。在此基础上,由Susan算子对上述两种可能的conner点进行处理,以提取出外围点和伪点,从而获得最佳匹配点。在海上安全应用方面的实验结果表明了该方法的有效性和可行性。

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