Revision history [back]

how to get a better binary image from low quality image?

I need to get contour from hand image, usually I process image with 4 steps:

1.get raw RGB gray image from 3 channels to 1 channel:

cvtColor(sourceGrayImage, sourceGrayImage, COLOR_BGR2GRAY);

2. use Gaussian blur to filter gray image:

 GaussianBlur(sourceGrayImage, sourceGrayImage, Size(3,3), 0);

3.binary gray image, I separate image by height, normally I split image to 8 pieces by its height, then each one I do threshold process: // we split source picture to binaryImageSectionCount(here it's 8) pieces by its height, // then we for every piece, we do threshold, // and at last we combine them agin to binaryImage

const binaryImageSectionCount = 8;
void GetBinaryImage(Mat &grayImage, Mat &binaryImage)
{
    // get every partial gray image's height
    int partImageHeight = grayImage.rows / binaryImageSectionCount;
    for (int i = 0; i < binaryImageSectionCount; i++)
    {
        Mat partialGrayImage;            
        Mat partialBinaryImage;
        Rect partialRect;
        if (i != binaryImageSectionCount - 1)
        {
            // if it's not last piece, Rect's height should be partImageHeight
            partialRect = Rect(0, i * partImageHeight, grayImage.cols, partImageHeight);
        }
        else
        {
            // if it's last piece, Rect's height should be (grayImage.rows - i  * partImageHeight)
            partialRect = Rect(0, i * partImageHeight, grayImage.cols, grayImage.rows - i  * partImageHeight);
        }

        Mat partialResource = grayImage(partialRect);    
        partialResource.copyTo(partialGrayImage);    
        threshold( partialGrayImage, partialBinaryImage, 0, 255, THRESH_OTSU);

        // combin partial binary image to one piece
        partialBinaryImage.copyTo(binaryImage(partialRect));

        ///*stringstream resultStrm;
        //resultStrm << "partial_" << (i + 1);
        //string string = resultStrm.str();

        //imshow(string, partialBinaryImage);
        //waitKey(0);*/
    }
    imshow("result binary image.", binaryImage);
    waitKey(0);
    return;
}

4. findcontour of binary image:

vector<vector<Point> > contours;        
findContours(binaryImage, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

normally it works fine, But for some low quality gray image, it doesn't work,like these below: lowqualityGrayImage1 lowqualityGrayImage2 lowqualityGrayImage3 lowqualityGrayImage4

because step 3 binary image is very bad, so step 4 cant get right contour of hand, the result of step3 is below:

binaryImage1 binaryImage2 binaryImage3 binrayImage4

Is there any way to get clean hand binary image? Thank you very much if you can give me any comment or help...

the complete code is below:

#include <opencv2/imgproc/imgproc.hpp>
#include<opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>

using namespace std;
using namespace cv;


// we split source picture to binaryImageSectionCount(here it's 8) pieces by its height, 
// then we for every piece, we do threshold, 
// and at last we combine them agin to binaryImage        
const binaryImageSectionCount = 8;
void GetBinaryImage(Mat &grayImage, Mat &binaryImage)
{
    // get every partial gray image's height
    int partImageHeight = grayImage.rows / binaryImageSectionCount;
    for (int i = 0; i < binaryImageSectionCount; i++)
    {
        Mat partialGrayImage;            
        Mat partialBinaryImage;
        Rect partialRect;
        if (i != binaryImageSectionCount - 1)
        {
            // if it's not last piece, Rect's height should be partImageHeight
            partialRect = Rect(0, i * partImageHeight, grayImage.cols, partImageHeight);
        }
        else
        {
            // if it's last piece, Rect's height should be (grayImage.rows - i  * partImageHeight)
            partialRect = Rect(0, i * partImageHeight, grayImage.cols, grayImage.rows - i  * partImageHeight);
        }

        Mat partialResource = grayImage(partialRect);    
        partialResource.copyTo(partialGrayImage);    
        threshold( partialGrayImage, partialBinaryImage, 0, 255, THRESH_OTSU);

        // combin partial binary image to one piece
        partialBinaryImage.copyTo(binaryImage(partialRect));

        ///*stringstream resultStrm;
        //resultStrm << "partial_" << (i + 1);
        //string string = resultStrm.str();

        //imshow(string, partialBinaryImage);
        //waitKey(0);*/
    }
    imshow("result binary image.", binaryImage);
    waitKey(0);
    return;
}


int main(int argc, _TCHAR* argv[])
{   
    // get image path
    string imgPath("C:\\Users\\Alfred\\Desktop\\gray.bmp");     

    // read image
    Mat src = imread(imgPath);
    imshow("Source", src);        
    //medianBlur(src, src, 7);  
    cvtColor(src, src, COLOR_BGR2GRAY);     
    imshow("gray", src);    

    // do filter
    GaussianBlur(src, src, Size(3,3), 0);   

    // binary image
    Mat threshold_output(src.rows, src.cols, CV_8UC1, Scalar(0, 0, 0)); 
    GetBinaryImage(src, threshold_output);
    imshow("binaryImage", threshold_output);

    // get biggest contour
    vector<vector<Point> > contours;    
    findContours(threshold_output,contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    int biggestContourIndex = 0;
    int maxContourArea = -1000;
    for (int i = 0; i < contours.size(); i++)
    {       
        if (contourArea(contours[i]) > maxContourArea)
        {
            maxContourArea = contourArea(contours[i]);
            biggestContourIndex = i;
        }
    }

    // show biggest contour
    Mat biggestContour(threshold_output.rows, threshold_output.cols, CV_8UC1, Scalar(0, 0, 0));
    drawContours(biggestContour, contours, biggestContourIndex, cv::Scalar(255,255,255), 2, 8, vector<Vec4i>(), 0, Point());
    imshow("maxContour", biggestContour);
    waitKey(0);

}