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This sample program loads an image and plots the graph of its horizontal or vertical projection
The Document contains an image and a projection vector.
When the Open command is sued, the image is loaded from a file.
Then, a projection along a r
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一种基于HSV颜色空间的车辆牌照提取方法
论文欢迎大家下载学习-According to the plate color, an approach of plate extract based on HSV color space is presented. By this approach, the color images coming
from the capture equipments are processed directly, so that the speed of p
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利用VC++对图像进行分析操作，包括阈值分割，投影检测（水平方向和垂直方向），差影检测，模板匹配-Using VC++ for image analysis operations, including the threshold segmentation, projection test (the horizontal direction and vertical direction), poor shadow detection, template matching
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一个车牌检测源码，通过水平投影和垂直投影来实现，识别率不高-A license plate detection source, through the horizontal projection and vertical projection to achieve the recognition rate is not high
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图像分割,阈值分析,水平垂直方向投影检测,差影检测,模板匹配-Image segmentation, threshold analysis, horizontal and vertical orientation projection test, and poor shadow detection, template matching
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用于对图像进行水平和垂直的直方图投影，用于差影检测和模板匹配-Is used to image the horizontal and vertical histogram projection for the poor shadow detection and template matching
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圖像水平與垂直投影-Image horizontal and vertical projection
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本程序采用一种基于垂直Sobel算子检测边缘和投影法的车牌定位方法,根据车牌区域竖直纹理突出的特点，利用Sobel垂直算子提取边缘，然后投影得到车牌的水平投影图，利用水平投影图分割出车牌，再运用膨胀运算进行车牌垂直定位。利用旋转投影法寻找车牌倾斜角度，然后用双线性插值进行车牌图像倾斜矫正。对经过精定位的车牌利用垂直投影法，找出各个字符的中心点，根据字符中心点位置进行切割。同时将切割出来的图片与数据库中的每张模板图片进行减法运算，计算该图片与模板的均方误差，其均方误差最小的模板即为识别出的字符。-
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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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这是一个车牌定位的小程序,利用水平投影法检测车牌水平位置-This is a small program, license plate location by using horizontal projection method to detect license plate horizontal position
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调用OPENCV库，使用水平法、垂直投影法进行图片分割，调试通过。使用class封装方法(Call OPENCV library, use the horizontal method, vertical projection method for image segmentation, debug and pass. Using class encapsulation method)
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