The proposed method is divided into two steps: 1 license plate location by the variance of gray image, and 2 license plate segmentation by connected components analysis and projection analysis.
该系统由两个重要步骤组成：1基于灰度方差的车牌定位算法，2结合连通域分析和投影分析的字符切分算法。
The proposed method analyses local image statistics and then matches the local histograms of two images to be fused by applying mean or mean variance matching normalization functions.
该方法分析了局部影像统计特性，应用均值或均值—方差匹配正态函数，对要融合的两幅影像局部直方图进行匹配。
In two-stage estimate, used orthogonal transformation to estimate aggregate average and fitting constants method to estimate variance which was unbiased.
在两步估计法中，利用正交变换得到了总平均的估计，然后采用拟合常数法得到了方差的估计，并证明了该估计是无偏估计。
In order to improve the robustness of this method, two-factor analysis of variance and additive model is proposed to reduce the impact of style information on face observed feature.
为了提高该方法的鲁棒性，通过两因子方差分析与加性模型分离人脸内因子与外因子，降低风格信息对人脸观察特征的影响。
In order to improve the robustness of this method, two-factor analysis of variance and additive model is proposed to reduce the impact of style information on face observed feature.
为了提高该方法的鲁棒性，通过两因子方差分析与加性模型分离人脸内因子与外因子，降低风格信息对人脸观察特征的影响。
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