搜索资源列表
opencvCar
- 开发环境:vc6.0 ,opencv1.0.整体功能:实现车牌跟踪,检测,车牌定位,车牌分割,字符 分割,字符识别,其中车牌跟踪和车牌检测不是很好,但是对于已经拍好的图片,车牌定位, 车牌分割,字符分割和字符识别效果很好。程序中的核心算法,本人已加详细注释。具体详见程序说明。希望对你有所帮助。-Development Environment: vc6.0, opencv1.0. Overall functions: license plate tracking, detect
opencvCar
- 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
Demo
- 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.
car-detecting_tracking
- 是为了实现车牌自动跟踪,检测,并拍照,定位,识别,但是跟踪和拍照等于没有实现-Is in order to realize the license plate automatic tracking, testing, and take photos, orientation, identification, but tracking and pictures is not implemented
Vehicle-license-recognition
- 车牌识别最基本的流程是:将采集后的图像二值化,然后依次经过车牌定位、字符分割、去除干扰,最后是字符识别-License Plate Recognition basic process is: after the acquisition of image binarization, followed through the license plate location, character segmentation, remove interference, and finally charact
LPRS-Python-opencv-
- 这个是自己用Python2.7写的基于opencv的车牌识别,目前识别率还是不怎么高,车牌定位采用的是形态学变换,分割是自己写的一个算法,识别部分采用的是kNN算法,有详细的注释!-This is his written in Python2.7 opencv based license plate recognition, the recognition rate is not very high, license plate location is the morphological tra
License-plate-location
- 车牌定位,可以有效地识别图像中的车牌,并准确定位。-License plate location, can effectively identify the image of the license plate, and accurate positioning.
opencvCar
- 本程序开发环境:vc和opencv 整体功能:是为了实现车载视频中车牌自动跟踪,检测,,定位,识别,视频中物体的跟踪必须是手动圈住才行,摄像头使用的是usb摄像头. 打开摄像头,可以看到视频中画面,移动鼠标圈住物体,可以自动跟踪。-This program development environment: VC and opencv The overall function: in order to realize the video vehicle license plate auto
LicenseplateRecognition
- 车牌牌照检测识别完整源代码 开发环境:vc6.0和opencv1.0 整体功能:是为了实现车牌自动跟踪,检测,并拍照,定位,识别,但是跟踪和拍照等于没有实现。 实现功能: 能实现视频中物体跟踪,但必须是手动圈住才行,摄像头是usb摄像头. 打开车牌图片,能进行定位,车牌分割,字符分割,字符识别。(License plate recognition)
cartest2
- 车牌定位,分割,实现了车牌的二值化 滤波、膨胀、腐蚀、等预操作,然后进行了定位于分割(The license plate location, segmentation, binarization of license plate Filtering, expansion, corrosion, pre operation, and then the positioning in the segmentationn)
opencv_car_location-master
- 可以识别出图片中的车牌号码,并定位到车牌号码的牌子的方框(opencv_car_location-master)
Python-opencv车牌识别
- 算法思想来自于网上资源,先使用图像边缘和车牌颜色定位车牌,再识别字符。车牌定位在predict方法中,为说明清楚,完成代码和测试后,加了很多注释,请参看源码。车牌字符识别也在predict方法中,请参看源码中的注释,需要说明的是,车牌字符识别使用的算法是opencv的SVM, opencv的SVM使用代码来自于opencv附带的sample,StatModel类和SVM类都是sample中的代码。SVM训练使用的训练样本来自于github上的EasyPR的c++版本。由于训练样本有限,你测试时会