Question

好吧所以我是opencv的新手，我已经设法执行了一个看起来好像＆＃34; ok＆＃34;对我而言，除了边缘变形外，我想要获得逼真的边缘，可能会模糊边缘以获得完美的图像，我注意到的另一件事是在我想要的整个过程之后颜色往往太亮了将活力降低到可以接受的程度以下是我的代码

private Bitmap backGrndErase()
{

    color = new Scalar(255, 0, 0, 255);
    dst = new Mat();
    Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.myshirt);
    Log.d(TAG, "bitmap: " + bitmap.getWidth() + "x" + bitmap.getHeight());


    bitmap = ResizeImage.getResizedBitmap(bitmap, calculatePercentage(40, bitmap.getWidth()), calculatePercentage(40, bitmap.getHeight()));



    bitmap = bitmap.copy(Bitmap.Config.ARGB_8888, true);
    Log.d(TAG, "bitmap 8888: " + bitmap.getWidth() + "x" + bitmap.getHeight());



    Mat img = new Mat();
    Utils.bitmapToMat(bitmap, img);


    Point p1 = new Point((img.cols()/10), (img.rows()/10));
    Point p2 = new Point((img.cols()-img.cols()/10), (img.rows()-img.rows()/10));
    Rect rect = new Rect(p1,p2);

    int border = 20;
    int border2 = border + border;
    Rect rect2 = new Rect( border, border, img.cols() - border2, img.rows()-border2);




    Mat mask = new Mat();
    debugger(""+mask.type());
    mask.setTo(new Scalar(125));
    Mat fgdModel = new Mat();
    fgdModel.setTo(new Scalar(255, 255, 255));
    Mat bgdModel = new Mat();
    bgdModel.setTo(new Scalar(255, 255, 255));

    Mat imgC3 = new Mat();
    Imgproc.cvtColor(img, imgC3, Imgproc.COLOR_RGBA2RGB);
    Log.d(TAG, "imgC3: " + imgC3);
    Log.d(TAG, "Grabcut begins");
    Imgproc.grabCut(imgC3, mask, rect2, bgdModel, fgdModel, 2, Imgproc.GC_INIT_WITH_RECT);
    Mat source = new Mat(1, 1, CvType.CV_8U, new Scalar(3.0));
    //Do Sth
    Core.compare(mask, source, mask, Core.CMP_EQ);
    //Do Sth
    Mat foreground = new Mat(img.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
    img.copyTo(foreground, mask);
    Imgproc.rectangle(img, p1, p2, color);

    Mat background = new Mat();
    try {
        background = Utils.loadResource(getApplicationContext(),
                R.drawable.blackcolor );
    } catch (IOException e) {

        e.printStackTrace();
    }
    Mat tmp = new Mat();
    Imgproc.resize(background, tmp, img.size());

    background = tmp;

    Mat tempMask = new Mat(foreground.size(), CvType.CV_8UC1, new Scalar(255, 255, 255));
    Imgproc.cvtColor(foreground, tempMask, 6/* COLOR_BGR2GRAY */);


    Mat vals = new Mat(1, 1, CvType.CV_8UC3, new Scalar(0.0));
    dst = new Mat();
    background.setTo(vals, tempMask);
    Imgproc.resize(foreground, tmp, mask.size());
    foreground = tmp;
    Core.add(background, foreground, dst, tempMask);
    Log.d(TAG, "Convert to Bitmap");


    //removing blackbaground started

     Mat tmp2 = new Mat();
     Mat alpha = new Mat();
     Imgproc.cvtColor(dst, tmp2, Imgproc.COLOR_BGR2GRAY);
     Imgproc.threshold(tmp2, alpha, 100, 255, Imgproc.THRESH_BINARY);


     List<Mat> rgb = new ArrayList<Mat>(3);
     Core.split(dst, rgb);


     List<Mat> rgba = new ArrayList<Mat>(4);
     rgba.add(rgb.get(0));
     rgba.add(rgb.get(1));
     rgba.add(rgb.get(2));
     rgba.add(alpha);
     Core.merge(rgba, dst);
     Bitmap output = Bitmap.createBitmap(dst.width(), dst.height(), Bitmap.Config.ARGB_8888);
     Utils.matToBitmap(dst, output);

    //removing back ended


    Utils.matToBitmap(dst, bitmap);



    //release MAT part
    img.release();
    imgC3.release();
    mask.release();
    fgdModel.release();
    bgdModel.release();
    alreadyRun = true;
    return  bitmap;

}

我在opencv网站上发布了相同的问题，但与此处的观众相比似乎较少，图片

Answer 1

试用代码只是为了显示您问题的一些可能性（假设背景将始终为白色）

#include "opencv2/opencv.hpp"

using namespace cv;

int main(int argc, char** argv)
{
Mat src= imread( argv[1] );
Mat original = src.clone();

imshow("source", src);

src = src + Scalar(40,40,40); // to remove jpeg artifacts

Mat mask;
cvtColor( src, mask, COLOR_BGR2GRAY );

mask = mask < 255;

add(src,Scalar(0,60,20),src,mask);

Mat blackbg = Mat::zeros(src.size(),CV_8UC3);
original.copyTo( blackbg, mask);

imshow("mask", mask);
imshow("changed color", src);
imshow("original image with black background", blackbg);
waitKey();

return 0;
}

Answer 2

如果你想非常精确地检测边缘或角落，opencv有一个子像素分辨率工具，在边缘检测之前应用高斯滤波器是个好主意，可以消除一些不良噪声

边缘细化OpenCV android

2 个答案: