一种基于DCT的梯度矢量流蛇目标边界检测方法

Jinshan Tang, S. Acton
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引用次数: 11

摘要

提出了一种基于离散余弦变换(DCT)的梯度矢量流(GVF)蛇形图像用于目标边界检测。为了开发DCT GVF蛇,我们对空间域中的每个像素计算其局部邻域的二维DCT。利用局部DCT系数的对比度度量来计算梯度矢量流场,并将其作为驱动蛇向目标边缘移动的外力。该方法的优点在于对乘性噪声具有较强的鲁棒性。将DCT GVF蛇形算法应用于带有乘性噪声图像的目标边界检测。实验结果表明,DCT GVF蛇的边界检测结果比原始GVF蛇的边界检测结果更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A DCT based gradient vector flow snake for object boundary detection
The paper proposes a new gradient vector flow (GVF) snake based on the discrete cosine transform (DCT) for object boundary detection. In order to develop the DCT GVF snake, for each pixel in the spatial domain, we compute the two dimensional DCT in its local neighborhood. A contrast measure derived from the local DCT coefficients is used to compute the gradient vector flow field, which is employed as the external force to drive the snake to the object edges. The advantage of the DCT GVF snake lies in its robustness to multiplicative noise. The DCT GVF snake is applied to object boundary detection in images with multiplicative noise. Experiments show the boundary detection result obtained by the DCT GVF snake is more accurate than that obtained by the original GVF snake.
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