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车牌识别算法,字符分割部分基于模板匹配法-License plate recognition algorithm, character segmentation is based in part on a template matching method
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基于opencv的车牌识别程序，能实现目标跟踪，截图，车牌识别包括了打开图像、图像二值化、车牌定位、字符分割、字符识别等。-Opencv-based license plate recognition program, to achieve the target tracking shots, license plate recognition, including the open image, image binarization, license plate localization, c
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针对车牌识别的字符bp神经网络训练，稍加改造即可用于ocr及其它字符识别场合将字符切分为32*16大小bbmp，放入相应文件夹，训练时选择该文件夹即可完成相应字符训练仅供学习使用，勿商业应用，本人保留所全部版权。
-License plate character recognition bp neural network training, a little transformation can be used for ocr character recognition occasions
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车牌的定位与分割，和使用BBP神经网络实现字符的识别。
-Positioning and segmentation of license plate character recognition and BBP neural network.
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用matlab做的车牌识别的,包括车牌定位位,二值化,滤波去噪,字符分割,识别,识别部分用的BP网
-License plate recognition using matlab, including the bit of license plate location, binarization, filtering, denoising, character segmentation, recognition, identify some with BP neural network
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图像分割程序源码代码说明P0801：索书号文字图像分割P0802：粘连字符切分P0803：文字识别P0804：彩色车牌分割P08805：商标文字分割Recognition：文字识别的识别子函数StrDeteect01：文字识别的结构特征提取子函数 可直接使用。
-Image segmentation program source code Descr iption P0801: Call text image segmentation P0802: adhesion character se
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索书号文字图像分割粘连字符切分文字识别彩色车牌分割商标文字分割割文字识别的识别子函数文字识别的结构特征提取子函数 已通过测试。
-Call text image segmentation adhesion character segmentation of a color license plate character recognition split the trademark text segmentation cut the text to identify the structur
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文字图像识别：索书号文字图像分割；粘连字符切分；文字识别；彩色车牌分分割；商标文字分割；文字识别的识别子函数；文字识别的结构特征提取子函数
-Text image recognition: Call text image segmentation Touching Character Segmentation character recognition color license plate sub-division trademark text segmentation char
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程序源码代码包含：索书号文字图像分割，粘连字符切分，文字识别，彩色车牌分割，，商标文字分割，文字识别的识别子函数，文字识别的结构特征提取子函数
-Call text image segmentation program source code contains: the adhesion character segmentation, character recognition, color license plate segmentation trademark text segmen
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功能很全的车牌识别系统，图像与处理，车牌定位，字符分割和字符识别等-Full license plate recognition system, image processing, license plate location, character segmentation and character recognition.
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车牌识别，对现有的车牌进行预处理，车牌定位，字符分割，字符识别-License plate recognition, license plate on the existing preprocessing, license plate location, character segmentation, character recognition
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车牌识别中，图像预处理、二值化，图像分割以及字符识别和分类的方法综述研究。并对主流方法进行了实现。-License plate recognition, image pre-processing, binarization, image segmentation and character recognition and classification Methods. And mainstream methods to achieve.
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确定车辆牌照在原始图像中的水平位置和垂直位置,从而定位车辆牌照,然后采用局部投影进行字符分割。在字符识别部分,提出了在无特征提取情况下基于支持向量机的车牌字符识别方法-Determine the horizontal position and vertical position of the vehicle license in the original image to locate the vehicle license, then the local projection characte
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1.首先单击载入图像菜单项（载入车辆图像）,图像在images文件夹下面。
2.然后单击车牌定位与识别单项，依次进行车牌提取、倾斜校正、字符分割、字符识别。
注：本程序使用的是OpenCV2.1版本，在没有安装此版本软件的机器上运行时需要将cv210.dll,cvaux210.dll,cvcore210.dll,highgui210.dll,ml210.dll这五个文件拷贝至*.exe可执行文件下。-First click Load Images menu items (lo
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主要用于车牌识别系统中的字符分割程序，算法自编的-Main character segmentation procedure for license plate recognition system, the algorithm self
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二值化、灰度拉伸、车牌定位、二值化、倾斜校正、字符分割、训练神经网络、识别字符-Binarization, gray stretch, license plate location, binarization, skew correction and character segmentation, training the neural network, identifying characters
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图像处理demo（谢凤英书），实现了包括灰度化、二值化、车牌定位、字符分割、字符识别在内的有关车牌识别的功能-Image processing demo (Xie Fengying book), including graying, binarization, plate location, character segmentation, character recognition, including the license plate recognition function
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提供一张包含车牌的照片（车牌占主要部分），能够准确定位并且实现字符分割。-Contains a photo of the license plate (license plate accounts for the main part), able to accurately locate and character segmentation.
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java车牌定位，灰度化，二值化，边缘处理，水平定位，垂直定位-java license plate location, graying, binarization, edge processing, horizontal position, vertical position, character segmentation
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有关车牌识别的程序，是支持向量机和神经网络一起写的。包括车牌的预处理、定位、分割、字符识别等。-For license plate recognition program, support vector machines and neural networks wrote together. Pretreatment including the license plate, positioning, segmentation and character recognition.
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