从二进制图像掩蔽blob [英] Masking a blob from a binary image

问题描述

我使用openCV和C ++做移动识别，我想创建一个蒙版或复制图像，以实现在提供的图片中看到的效果。 。以下是图片的解释
生成的人行走的斑点被看到。然后，创建原始帧的掩模图像或复制图像，现在掩蔽二进制人blob，并且现在将非掩蔽像素设置为零。结果是用黑色背景提取人体。下图显示了如何提取人类blob，然后屏蔽人类blob。
这将对视频序列的每第5帧进行。我的代码到目前为止包括获取每5帧，灰度，找到所有的斑点的区域，并应用阈值来获得一个二进制图像，或多或少，只有人的Blob是白色的，其余的图像黑色。现在，我试图提取人体，但我没有线索如何进行。请帮助我。

I am doing motion recognition of walking using openCV and C++ and I would like to create a mask or copied image in order to achieve the effect seen in the picture provided. .The following is an explanation of the images The resulting blob of the human walking is seen. Then, a mask image or copied image of the original frame is created, the binary human blob is now masked and the non-masked pixels are now set to zero. The result is the extracted human body with a black background. The diagram below shows how the human blob is extracted and then masked. This is to be done for every 5th frame of a video sequence. My code so far consists of getting every 5th frame, grayscaling it, finding the areas of all the blobs, and applying a threshold value to get a binary image where more or less, only the human blob is white and the rest of the image is black. Now, I am trying to extract the human body but I have no clue how to proceed. Please help me.

#include "cv.h"
#include "highgui.h"
#include "iostream"

using namespace std;
int main( int argc, char* argv ) {

CvCapture *capture = NULL;
capture = cvCaptureFromAVI("C:\\walking\\lady walking.avi");
if(!capture){
    return -1;
}

IplImage* color_frame = NULL;
IplImage* gray_frame = NULL ;

int thresh_frame = 28;
CvMoments moments;

int frameCount=0;//Counts every 5 frames
cvNamedWindow( "walking", CV_WINDOW_AUTOSIZE );

while(1) {
    color_frame = cvQueryFrame( capture );//Grabs the frame from a file
    if( !color_frame ) break;
    gray_frame = cvCreateImage(cvSize(color_frame->width, color_frame->height), color_frame->depth, 1);
    if( !color_frame ) break;// If the frame does not exist, quit the loop


    frameCount++;
    if(frameCount==5)
    {
        cvCvtColor(color_frame, gray_frame, CV_BGR2GRAY);
        cvThreshold(gray_frame, gray_frame, thresh_frame, 255, CV_THRESH_BINARY);
        cvErode(gray_frame, gray_frame, NULL, 1);
        cvDilate(gray_frame, gray_frame, NULL, 1);

        cvMoments(gray_frame, &moments, 1);
        double m00;
        m00 = cvGetCentralMoment(&moments, 0,0);

        cvShowImage("walking", gray_frame);
        frameCount=0;
    }
    char c = cvWaitKey(33);
    if( c == 27 ) break;
}

double m00 = (double)cvGetCentralMoment(&moments, 0,0);
cout << "Area - : " << m00 << endl;
//area of lady walking = 39696. Therefore, using new threshold area as 30 for this video
//area of walking man = 67929

cvReleaseImage(&color_frame);
cvReleaseImage(&gray_frame);
cvReleaseCapture( &capture );
cvDestroyWindow( "walking" );

return 0;
}

我也想上传我在代码中使用的视频，我不知道如何上传到这里，所以如果有人可以帮助我。我想提供尽可能多的信息w.r.t.我的问题。

I would also like to upload the video that I am using in the code but I don't know how to upload it here, so if anyone can help me out with that too. I want to provide as much info as possible w.r.t. my question.

推荐答案

最简单的方法是查找图像中最大的blob（cvfind轮廓可以是你需要的功能），然后你设置为blac所有其他blob（扫描所有轮廓和使用cvfloadfill）。
最后你扫描整个二进制图像，如果考虑的像素是白色你什么也不做，如果像素是黑色你设置为黑色的第5帧的相应像素

the easiest way is to look for the biggest blob in the image (cvfind contours can be the function you need), then you set to blac all the other blobs (scannig all the contours and using cvfloadfill). finally you scan the entire binary image if the considered pixel is white you do nothing, if the pixel is black you set to black the corresponding pixel of the 5th frame

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