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source
- 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。-1 First, click Load Image menu item (loaded vehicle image), the image in the images folder below. 2, and then click the individual license plate location and recognition
chepaishibie
- 用于车牌识别，并标记处车牌区域，将车牌提取出来-For license plate recognition, license plate and mark the area, the license plate is extracted
chepaishibie
- 车牌提取：利用车牌的颜色、面积、长宽以及宽高比等特征对车牌区域进行提取，其中主要用到了二值图像的开闭运算技术。实验用的车牌均为白字蓝底，因此可以先找到图像中的蓝色区域，生成一张蓝色区域识别二值图，若判定为蓝色，值为1，若判定为非蓝色，值为0。利用开闭运算，对图像做预处理，然后再利用车牌的其他物理特征对车牌区域作进一步的识别。-Plate Extraction: Using color plates, area, length and width and aspect ratio and othe
LPR
- 对拍摄的图像进行车牌提取，2值化，形态学处理，后用轮廓定位定位出车牌位置，最后提取-Images captured license plate extraction, binarization, morphological processing, after the license plate with the outline of positioning positioning location, and finally extract
License-plate-recognition-system
- 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。-License plate location and recognition of license plate extraction, followed by individual, tilt correction, character segmentation, character recognition.
License-plate-recognition
- 车牌识别软件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。-License plate recognition software 1. First click Load Image menu item (loaded vehicle images), the image in the images folder. 2. Then click the license plate l
car
- matlab车牌提取算法，含所有源代码，全部调试通过。-Matlab license plate extraction algorithm, containing all the source code, all debugging through.
Vehicle-license-plate-recognition
- 车牌识别技术是计算机视频图像识别技术在车辆牌照识别中的一种应用。车牌识别技术要求能够将运动中的汽车牌照从复杂背景中提取并识别出来，通过车牌提取、图像预处理、特征提取、车牌字符识别等技术，识别车辆牌号、颜色等信息-License Plate Recognition Vehicle (VLPR) is an application of computer video image recognition technology in vehicle license plate recognition.
windoeslock
- 这是一个给予opencv的车牌识别程序，可以OCR车牌提取字符-this is a program that ...
chepaishibieCPP
- 一、车型识别 1.首先单击车型识别菜单下的载入图像菜单项（载入背景和前景图像）。 2.然后单击车辆提取菜单项，依次进行图像做差、二值化、开运算、图像去噪、图像填充处理，轮廓提取。 3.最后单击车型识别菜单项，对车辆进行识别。 4.测试图像存储在img文件夹下，车型轮廓模板存储在contour文件夹下。 二、车牌识别 1.先打开一幅图片，然后在车牌定位与识别菜单下依次点击：车牌提取、倾斜校正、字符分割、字符识别。 2.测试图像存储在img文件夹下。
image-segmentati
- 车牌图像分割识别，从图片上把字符提取出来，用于车牌提取。-License plate image segmentation recognition, the picture to extract the characters for license plate extraction.
CarNumber
- 本算法进行车牌识别，首先提取车牌的位置，然后对车牌的字符进行分割，最后进行识别，将识别结果输出。本算法能得到较好的识别结果。(The algorithm for license plate recognition, the first extraction of the location of the license plate, and then the license plate character segmentation, and finally identify the recogni
test5
- 基于图像处理的方法实现车牌图像的矫正和提取(Realization and Extraction of License Plate Image Based on Image Processing)
License Plate Recognition
- 在一张含有汽车车牌的图像中，提取车牌及车牌中的汉字和车牌号（车牌汉字识别的不是很完美）(In an image containing a car license plate, the extraction license plate and license plate in the Chinese characters and license plate number (license plate Chinese character recognition is not perfect))
matlab
- 索书号文字图像分割，粘连字符切分，彩色车牌分割 ，文字识别的结构特征提取子函数(Call text image segmentation, character segmentation, color plate segmentation, text recognition feature extraction Functions)
字符特征提取
- 结合OpenCV在VS2015平台上对含有字符特征提取，例如可以进行车牌识别等(Combined with OpenCV on the VS2015 platform to contain character feature extraction, such as license plate recognition can be carried out)
无语音读取简化版本
- matlab实现基于模板的车牌识别.主要模块如下：颜色信息提取、车牌区域定位、识别、提取、检测倾斜度、车牌校正、车牌区域2值化、擦除干扰区域、文字分割、模版匹配、结果输出。(Matlab based template based license plate recognition.The main modules are as follows: color information extraction, license plate location, recognition, extractio
Plate-Location-master
- 对照片进行形态学处理，提取感兴趣的区域，实现车牌的提取(The image is processed by morphology, the region of interest is extracted, and the extraction of the license plate is realized.)
car_plate
- 数字图像处理仿真，在复杂背景环境下提取出车辆牌照上的信息(Extraction of information on vehicle license plate in complex background environment)
IMAGE_MATLAB_GUI
- 功能强大的gui,各种处理图像的程序，比如中值滤波、灰度化、格式转换、边缘检测等，并且列举了四个特别好的实例，比如人脸识别、车牌提取等(Powerful GUI, various programs for image processing, such as median filtering, grayscale, format conversion, edge detection, etc., and enumerate four very good examples, such as face