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Integral image based fast algorithm for two-dimensional Otsu thresholding

机译:基于积分图像的二维Otsu阈值快速算法

摘要

As the classic image segmentation technique, Otsu adaptive thresholding method is widely employed in image processing and computer vision. Two-dimensional Otsu thresholding algorithm was regarded as an effective improvement of the original Otsu method, especially under low SNR condition. However, the tremendous computation cost limited the application of two-dimensional Otsu algorithm in real-time situation. This paper addresses this problem and proposes a novel fast algorithm. We utilized integral image to simplify the redundant calculation for searching optimal threshold Instead of repeating accumulations, the sum of rectangle area can be calculated by several addition operations. Both the theoretical analysis and segmentation experiment proved that the proposed approach can significantly reduce the computation cost and still obtain the identical optimal threshold acquired by original two-dimensional Otsu algorithm.
机译:作为经典的图像分割技术,大津自适应阈值化方法已广泛应用于图像处理和计算机视觉中。二维Otsu阈值算法被认为是对原始Otsu方法的有效改进,尤其是在低SNR条件下。然而,巨大的计算成本限制了二维Otsu算法在实时情况下的应用。本文解决了这一问题,并提出了一种新颖的快速算法。我们利用积分图像简化了用于搜索最佳阈值的冗余计算,而不是重复累加,可以通过几次加法运算来计算矩形面积的总和。理论分析和分割实验均证明,该方法可以显着降低计算成本,并且仍能获得与原始二维Otsu算法相同的最优阈值。

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