First, a method to estimate the local image gradient, called the BEG (best estimation of gradient) algorithm was proposed to extract the texture orientation parameters.

首先提出了局部图像的梯度估计方法，称之为BEG(梯度的最佳估计)算法，用来提取图像的纹理方向特征参数。

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Using images' features such as gradient, mean, variance, degree of smoothing and texture characteristics to establish cost function may obtain the best results of target detection.

该方法利用动态规划理论中代价函数的建立过程来充分考虑图像中的灰度、均值、方差、光滑程度和纹理等多种特征，从而使目标检测的结果为最佳。

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