车牌识别机器学习方法的数学建模与实现

首先,针对不同光照、复杂背景和投影失真的车牌图像建立基于Adaboost算法和改进Haar特征的车牌检测模型;然后,运用Radon变换进行车牌校正,并结合3次B样条小波变换和识别反馈模型对字符进行粗和精分割;最后,根据汉字和数字字母的不同结构特征,采用不同的算法提取特征,特别是针对车牌字符特点,训练汉字、字母和数字字母3种神经网络模型用于建立字符识别模型.实验结果表明该模型是实用的.     

基于SVM的车牌数字识别方法

运用支持向量机对车牌字符进行识别,解决了由于图像受客观条件的影响、样本数量不是很大等原因导致的识别率不高的问题.主要针对车牌字符中的数字进行实验,选取了15组数字样本,8组进行训练,7组进行测试,采用交叉验证的思想对SVM进行参数C与g的寻优,并选择合适的核函数,对样本进行训练和预测,对于某些数字的识别率可达到100%,并在相同的训练集和测试集下与BP网络的识别效果进行对比.实验结果表明,SVM在训练样本较少且无字符特征提取的情况下具有很好的识别率,并且有很好的分类推广能力.     

一种快速有效的混合倾斜车牌校正方法

车牌倾斜校正是车牌识别系统中的一关键技术,校正效果将直接影响到后续字符分割和识别的效果.为此,提出了一种快速有效的混合倾斜车牌校正方法.水平倾斜校正时,先进行Sobel垂直边缘检测算子提取字符的有效数据点,构造有效数据点矩阵,然后进行矩阵奇异值分解,利用特征向量矩阵导出车牌水平倾斜角度的表达式;垂直倾斜校正时,首先通过Sobel垂直和水平边缘检测有效去除边框及上下左右噪声干扰区域,然后通过形态学腐蚀提取有效反映字符水平错位的有效数据点,其次将这些有效数据点水平投影分成七个字符区域,求取每个区域错切变换后的最佳列坐标质心对应其区域垂直倾斜角,最后取区域垂直倾斜角的均值作为车牌的最佳垂直倾斜角.对大量复杂背景下的倾斜车牌进行实验,并做了精确度、运行时间、抗干扰性分析,实验结果表明:提出的混合倾斜校正方法精确度高、运行时间短、抗干扰性强.     

模拟试卷

一、以下各题每小题5分共20分.1.求极限.2.设在 点连续而不可导,求.3.求 上的最大值与最小值.     

两个广泛相依随机变量在最值运算下的次指数性

本文主要研究一类广泛相依结构下两个次指数随机变量的最小值、最大值关于次指数族的封闭性.证明了在该相依结构下两个次指数随机变量的最小值总是次指数的,给出了该相依结构下两个次指数随机变量的最大值为次指数分布的一个充分必要条件,推广了已有结果,同时表明该相依结构对两个次指数分布在最值运算下的次指数性是不敏感的.     

善用一个模型,巧解一类题

求线段的最值,同学们往往感到困难,对于一类求线段的最大值和最小值得问题可以利用以下模型求解.一、建立模型已知:线段AB=6,线段AC=4,固定线段AB,将线段AC绕点A旋转,探求线段BC的最大值和最小值.分析为了求到线段BC的最大值和最小值,先构造一个含有线段BC的三角形,而且另外两条边是有数值的线段,如图1(1).线段AC绕点A旋转,当C落到BA延长线上     

二次函数中最值问题的求解

<正>与最大值和最小值有关的问题,或极大和极小的问题一直是中考的热点问题,下面就北京近几年的中考和模拟考试中以二次函数图像为背景的几个试题作一阐释.例1如图1,已知抛物线y=x2+bx+c与x轴交于A、B两点,AB=2,与y轴交于点C,对称轴为直线x=2.(1)求抛物线的表达式.(2)设P为对称轴上一动点,求△APC周长的最小值.     

解函数复合最值问题的常用策略

在数学竞赛和高考题中,常常会遇到一些在一类最大值中求其最小值或在一类最小值中求其最大值的复合最值问题.它是函数最值中的一种特殊类型,解决这类问题的方法也比较特殊.本文介绍解决此类问题的一些常用策略.     

双层最值问题的解题策略

双层最值也称复合最值,是指在给出的多个式子中,求这些式子中最大值中的最小值或求最小值中的最大值．这类问题在数学竞赛和高考中都有出现,学生对此常感到束手无策,本文通过几道例题,谈谈求双层最值问题的几种策略．     

用向量数量积解决线性规划应用题

<正>实际生产与生活中有许多线性规划应用问题,其一般求解步骤是:(1)根据题意,建立数学模型,作出不等式组所表示的可行域;(2)设所求目标函数f(x,y)的值为z;(3)将各顶点坐标代入目标函数,即可得到z的最大值与最小值,或求直线f(x,y)=z在y轴上截距的最大值(最小值),从而求得z的最大值与最小值;(4)检验最优解是否符合实际意义.     

基于DCT变换的车牌定位算法

车牌定位技术是车牌识别技术中最重要的部分,利用车牌图像在DCT域的水平和竖直能量值对图像进行进一步二值化处理,通过中值滤波和小区去除定位车牌.实验结果表明这种车牌定位方法具有算法实现简单、速度快、适应性强的特点.     

修正主成分分析及其在车牌定位中的应用

车牌照识别技术是现代智能交通的重要组成部分.为了从彩色图像中定位及分割出汽车牌照,将图像中每一个像素点的红、绿、蓝值看成三维空间中的点(r,g,b),采用主成分分析对含牌照的彩色图像进行正交变换得到(r′,g′,b′),分别以r′,g′,b′作为灰度值得到三个主成分图像,牌照信息体现在第二主成分图像中.为了进一步提高车牌定位效率,对正交变换矩阵进行了修正,对修正后的第二主成分图像进行二值化,分割出白色区域即可定位出汽车牌照.实验表明,本算法对噪声不敏感,抗干扰性强,识别效率高.     

Crucial combinations of parts for handwritten alphanumeric characters

A combining approach has been studied previously to integrate different parts of handwritten characters for their analysis and recognition. Perfect combinations, by which the characters can be identified with certainty, are important to pattern analysis and character recognition. However, a large number of possible combinations (e.g., 63 combinations for a character partitioned into six parts), also produce a lot of perfect combinations. Hence, it is necessary to determine which of them are most important. In this paper, we propose a methodology of finding the basic crucial combinations, and algorithms to compute them. Compared with perfect combinations, such basic crucial combinations are most significant to the character distinctiveness. Similarly, the largest confusion regions are also identified.Experimental studies have also been conducted using the 89 most frequently used patterns of 36 alphanumeric handprints, to obtain their basic crucial combinations and largest confusion combinations. The results indicate that the ratio of the number of basic crucial combinations to perfect combinations is only 12.6%, and the ratio of the number of the largest confusion regions to the total confusion combinations is 15.6%.     

基于剪枝信任度传播的手写体目标形状匹配方法

手写体识别中,目标形状的匹配是较为重要的工作.为了提高手写体目标形状的匹配速度,提出一种新的匹配方法.由于手写体目标形状的几何先验知识已知,并可以采用少量的参数进行表示,新方法采用参数化可变形模板匹配目标形状,确定其后验概率模型,并定义剪枝信任度空间,依据信任度传播算法的特性,首次将剪枝信任度传播算法应用于求解可变形模板与目标形状之间的最佳匹配.实验结果显示,在灰度图像中,对手写体目标形状的轮廓检测与定位速度显著提高.提出将剪枝信任度传播方法应用于手写体目标形状的匹配工作,能够使得目标形状填补空白,应用于相关性较为稀疏的图模型中.     

BP模式识别与Hopfield联想记忆识别能力的比较

神经网络可以进行模式识别,这一功能具有很高的实用价值.主要研究BP神经网络和离散Hopfield神经网络的识别能力.BP网络是前向神经网络,使用的是监督式学习规则.离散Hopfield是一种反馈网络,结构上输入、输出节点相连使得网络系统的输出状态具有动态变化特性.就数字,字母,手写体数字比较了BP网络和离散Hopfield网络的识别能力,得到了可观的结论,对两个网络的应用做更进一步的阐述.     

Application of Postnikov’s formula for estimation of short sums of Dirichlet characters over shifted prime numbers

Estimates of short sums of Dirichlet characters over shifted prime numbers are obtained in the case when the modulus of a character is a power of a fixed prime number.     

The degree of the special linear characters of a rank two free group

Given a word W in the free group on 2 letters F ₂, Horowitz showed that the special linear character of W is an integer polynomial in the 3 characters of the basic words of F ₂. Special linear characters are defined via the trace of their representations, and the polynomial character of an arbitrary W can be found by application of certain “trace relations”, which allow one to write the character of a complicated word as a sum of products of the characters of simpler words. Even in the n = 2 case, where the polynomial is uniquely defined, this procedure can be difficult and tedious. In this note, we use the structure of a free group word in F ₂ to compute the degree and the leading monomial of its SL(2,\mathbbC){SL(2,\mathbb{C})} -character without actually computing the full polynomial.     

A fuzzy rule-based system for handwritten Chinese characters recognition based on radical extraction

In this paper, a fuzzy rule-based system for handwritten Chinese characters recognition (HCCR) based on radical extraction is proposed. Since the writings of handwritten Chinese characters vary a lot, we adopt fuzzy set theory to deal with the recognition of these fuzzy patterns. Candidates of strokes are provided with confidence values to obtain more reliable and accurate results. Furthermore, hierarchical fuzzy rule sets that represent the character structures are used to combine the extracted strokes into compound strokes or radicals. The flexible expansion ability thus provided is very promising. Also, since the number of rules in a fuzzy system is much less than that in a general rule-based system, the computation effort is not difficult. An average of 99.63% recognition rate of 542 test categories that are selected from the 100th sample set of HCCRBASE (character image database provided by CCL, ITRI, Taiwan) is obtained. The experimental results not only verify the feasibility of the proposed system, but also suggest that applying fuzzy set theory to HCCR is an efficient and promising approach.