标准人 meaning in Chinese
standard life assurance
Examples
- On the basis of the ratio of different age in statistical yearbook , author creates a method of the financing of social security for fictitious person , in order to avoid accuracy being disturbed by the difference among particular farmers
本文以人口统计年鉴中不同年龄段人口所占比例为基数，创建了虚拟合理标准人的测算方法，规避被征地农民群体个体之间存在的差异对准确推算保障所需资金的干扰。 - Standard face images are formed through the above - mentioned processing . during the feature extraction , for those standard face images , regarding the between - class scatter matrix as generating matrix , we extract the algebraic features of face images through k - l transform and singular value decomposition
在人脸特征提取过程中，对经过预处理的标准人脸图像，以类间散布矩阵为产生矩阵，通过k - l变换降维并结合奇异值分解来提取人脸代数特征。 - In the course of image preprocessing , digital face images are captured with a numeral camera and these images are transformed to 8 bit from 24 bit . then the noise in face images are removed by using the method of median filter and the face images are binarized . finally the face in each face image are segmented with the method of integration projection , then standardized
在图像预处理过程中，首先利用数码相机获取人脸数字图像，然后将24位图像转换成256级灰度图像，并利用中值滤波的方法对图像进行去噪处理，接着对图像进行二值化处理，最后采用积分投影的方法将人脸分割出来并进行归一化，最终得到标准人脸图像。 - Then , lda is followed and employed for the second feature extraction in the transformed space . based on this framework , a combinatorial optimal lda ( olda ) algorithm is proposed . experiments is performed on orl face image database as well as nust603 face image database , and the experimental results indicate that olda is robust , efficient and superior to the previous lda - based methods in terms of recognition accuracy
进一步地，在该理论框架下，具体给出了处理高维、小样本问题的组合最优的线性鉴别分析算法，在orl标准人脸库和nust603人脸库上的试验结果证实了该方法的卓越性能，在识别率方面均优于以往的同类方法。 - Rather , in this paper , two straightforward image projection techniques , termed image principal component analysis ( 1mpca ) and image fisher linear discriminant analysis ( imlda ) , are respectively developed to overcome the weakness of the conventional pca and lda as applied in image feature extraction
在orl标准人脸库和nust603人脸库上的试验结果表明，与通常的主分量分析与线性鉴别分析方法相比，图像投影鉴别分析与主分量分析技术将特征抽取的速度提高了一个数量级以上。不仅如此，其识别精度依然高于传统的eigenfaces与fisherfaces方法。