我是新的opencv.我写一个删除背景.
我的输入图片
我将我的程序编码为以下步骤:
- 计算平均像素
//define roi of image
cv::Rect roi(0, 0, 20 , 20 );
//copies input image in roi
cv::Mat image_roi = imgGray( roi );
//imshow("roi", image_roi);
//computes mean over roi
cv::Scalar avgPixelIntensity = cv::mean( image_roi );
//prints out only .val[0] since image was grayscale
cout << "Pixel intensity over ROI = " << avgPixelIntensity.val[0] << endl;
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- 根据平均像素值创建新的Mat图像:
//create new mat image base on avgPixelIntensity
cv::Mat areaSampleArv(imgGray.rows, imgGray.cols,imgGray.type(),avgPixelIntensity.val[0]);
imshow("areaSampleArv", areaSampleArv);
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- 反转图片:
void image_invert(Mat& image){
int height, width, step, channels;
uchar *data;
height = image.cols;
width = image.rows;
step = (int)image.step;
channels = image.channels();
data = (uchar *)image.data;
for(int i = 0; i < height; i++){
for(int j = 0; j < width; j++){
for(int k = 0; k < channels; k++){
data[i*step + j*channels + k] = 255 - data[i*step + j*channels + k];
}
}
}
//imwrite("/Users/thuydungle/Desktop/1234/inverted.png", image);
imshow("inverted", image);}
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我的图像反转结果: 
- 用原始图像添加倒置图像:
Mat dst;
dst = areaSampleArv + im0;
imshow("dst", dst);
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任何我的图像结果: 
看起来非常糟糕,我可以使用阈值来提取数字吗?
所以,你能告诉我如何解决它吗?
谢谢 !
您可以尝试cv:inRange()基于颜色的阈值.
cv::Mat image = cv::imread(argv[1]);
if (image.empty())
{
std::cout << "!!! Failed imread()" << std::endl;
return -1;
}
cv::Mat threshold_image;
// MIN B:77 G:0 R:30 MAX B:130 G:68 R:50
cv::inRange(image, cv::Scalar(77, 0, 30),
cv::Scalar(130, 68, 50),
threshold_image);
cv::bitwise_not(threshold_image, threshold_image);
cv::imwrite("so_inrange.png", threshold_image);
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int erode_sz = 4;
cv::Mat element = cv::getStructuringElement(cv::MORPH_ELLIPSE,
cv::Size(2*erode_sz + 1, 2*erode_sz+1),
cv::Point(erode_sz, erode_sz) );
cv::erode(threshold_image, threshold_image, element);
cv::imwrite("so_erode.png", threshold_image);
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cv::dilate(threshold_image, threshold_image, element);
cv::imwrite("so_dilate.png", threshold_image);
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cv::imshow("Color Threshold", threshold_image);
cv::waitKey();
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您也可以执行cv::blur(threshold_image, threshold_image, cv::Size(3, 3));后cv::bitwise_not()得到一个稍微好一点的结果.
改变代码的乐趣.
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