pattern n. 1.模范,榜样;典范。 2.型,模型;模式;雏型;【冶金】原型。 3.花样;式样;(服装裁剪的)纸样;图案,图谱,图表;机构,结构;特性曲线;晶体点阵;(电视的)帧面图像。 4.方式;形式;格局;格调。 5.(衣料等的)样品,样本,样板。 6.〔美国〕一件衣料。 7.(炮弹等的)散布面;靶子上的弹痕。 8.(飞机的)着陆航线。 a pattern wife 模范妻子。 a paper pattern for a dress 女服纸样。 a machine of a new [an old] pattern新[旧]型机器。 a cropping pattern农作制。 after the pattern of 仿…。 vt. 1.照图样做;仿造,摹制 (after; upon)。 2.给…加花样,用图案装饰。 3.〔英方〕与…相比 (to, with)。 vi. 形成图案。 pattern oneself after 模仿,学…的榜样。 adj. -ed 仿造的;被组成图案的(patterned forms【语言学】 仿造词)。 n. -ing 图案结构,图形;(行为等的)特有型式。 adj. -less 无图案的。
Classifier is an important ingredient in pattern recognition . among all the classifiers, linear classifiers are paid great attention in statistical pattern recognition due to their simplicity and easy expansibility to nonlinear classifiers 在模式识别系统中,分类器是一个重要的组成部分,分类器设计的好坏将直接影响模式识别系统最终的识别性能。
A survey of character recognition methods is presented in chapter 3 . comparison of some extracted feature matching algorithms based on statistical pattern recognition is conducted . these features are profile, mesh and projection of micro structure for distinguishing similar characters 作者对车牌汉字识别的特征提取方法进行了研究,首先比较了多种基于统计模式识别的特征提取匹配算法,包括外围面积特征,网格特征和用于区分相似汉字的微结构投影特征。
In statistical pattern recognition algorithm, the system makes geometry and grey standardize on the images located, then extracts their features base on three kinds of integration projection curve . at last matches them with the feature samples in sample library and output the most suitable image 在人脸的统计识别算法中,系统对定位后的人脸图像做几何标准化与灰度标准化处理,并基于三类积分投影曲线抽取人脸特征,与样本库中的特征样本进行匹配,选取最为匹配的人脸图像作为输出。
In theory, based on the characteristic detection probability model of sar image, the ability of distinguishing two connected resolution unit and detecting point target is discussed firstly . then we do conclude that the high precision classification algorithms can build up based on pixel level, which combine three characteristics : the main characteristic ( the rcs statistical distribution ), two assistant characteristics ( the shadow and structure model ) . secondly, the practical problems of the three pattern classification technologies ( statistical pattern recognition, neural network, fuzzy neural network ) for the sar image are analyzed 在此基础上,结合sar图像其它固有特性研究,提出了以rcs的统计分布特性作为主要特征,阴影和高分辨率条件下的区域结构特征作为提高分类精度的辅助特征,并将二者有机结合起来进行分类方法研究的思路;分析了统计模式识别、神经网络和模糊技术应用到sar图像地物分类中需要解决的实际问题;提出了在图像域对sar图像质量指标近似计算和分类率的具体评估方法。