i've recently switched to Emgu CV from OpenCv.. in opencv, i calculated absolute difference using cvAbsDiff(Frame1,Frame2,foreground);
and i could check the value of frame difference as: if(cvNorm(frame2,frame1) > xyz){ ... }
and here in Emgu cv, i've calculated as: Difference = Previous_Frame.AbsDiff(Frame);
as explained Here the type of Difference is Image .. i want to know, how can i get the value (double) of difference??
Thanks :)
Can you clarify your question a little bit more?
But using CvInvoke, you can do:
CvInvoke.cvAbsDiff(frame1, frame2, foreground);
double valueInDouble = CvInvoke.cvNorm(frame1, frame2, NORM_TYPE.CV_DIFF, IntPtr.Zero);
if (valueInDouble < xyz){}
Mask is an optional parameter(set to NULL in OpenCV documentation), so you can set it to IntPtr.Zero
Related
I am doing a 6-dof transformation with the RANSAC given in OpenCV and I now want to convert two matrices of cv::Mat to an Isometry3d of Eigen but I didn't find good examples about this problem.
e.g.
cv::Mat rot;
cv::Mat trsl;
// the rot is 3-by-3 and trsl is 3-by-1 vector.
Eigen::Isometry3d trsf;
trsf.rotation = rot;
trsf.translation = trsl; // I know trsf has two members but it seems not the correct way to do a concatenation.
Anyone give me a hand? Thanks.
Essentially, you need an Eigen::Map to read the opencv data and store it to parts of your trsf:
typedef Eigen::Matrix<double, 3, 3, Eigen::RowMajor> RMatrix3d;
Eigen::Isometry3d trsf;
trsf.linear() = RMatrix3d::Map(reinterpret_cast<const double*>(rot.data));
trsf.translation() = Eigen::Vector3d::Map(reinterpret_cast<const double*>(trsl.data));
You need to be sure that rot and trsl indeed hold double data (perhaps consider using cv::Mat_<double> instead).
Say I have a very simple image or shape such as this stick man drawing:
I also have a library of other simple images which I want to compare the first image to and determine the closest match:
Notice that the two stick men are not completely identical but are reasonably similar.
I want to be able to compare the first image to each image in my library until a reasonably close match is found. If necessary, my image library could contain numerous variations of the same image in order to help decide which type of image I have. For example:
My question is whether this is something that OpenCV would be capable of? Has it been done before, and if so, can you point me in the direction of some examples? Many thanks for your help.
Edit: Through my searches I have found many examples of people who are comparing images, or even people that are comparing images which have been stretched or skewed such as this: Checking images for similarity with OpenCV . Unfortunately as you can see, my images are not just translated (Rotated/Skewed/Stretched) versions of one another - They actually different images although they are very similar.
You should be able to do it using feature template match function of OpenCV. You can use matchTemplate function to look for the feature and then, minMaxLoc to find its location. Check out the tutorial on OpenCV web site for matchTemplate.
seems you need feature points detections and matching. Check these docs from OpenCV:
http://docs.opencv.org/doc/tutorials/features2d/feature_detection/feature_detection.html
http://docs.opencv.org/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.html
For your particular type of images, you might get good results by using moments/HuMoments for the connected components (which you can find with findContours).
since there is a rotation involved, I dont think template matching would work well. You probably need to use Feature point detection such as SIFT or SURF.
EDIT: This won't work with rotation. Same for matchTemplate. I am yet to try the findContours + moments as in bjoernz answer which sounds promising.
Failed Solution:
I tried using ShapeContextDistanceExtractor(1) available in OpenCV 3.0 along with findContours on your sample images to get good results. The sample images were cropped to same size as original image(128*200). You can could as well use resize in OpenCV.
Code below compares images in images folder with 1.png as the base image.
#include "opencv2/shape.hpp"
#include "opencv2/opencv.hpp"
#include <iostream>
#include <string>
using namespace std;
using namespace cv;
const int MAX_SHAPES = 7;
vector<Point> findContours( const Mat& compareToImg )
{
vector<vector<Point> > contour2D;
findContours(compareToImg, contour2D, RETR_LIST, CHAIN_APPROX_NONE);
//converting 2d vector contours to 1D vector for comparison
vector <Point> contour1D;
for (size_t border=0; border < contour2D.size(); border++) {
for (size_t p=0; p < contour2D[border].size(); p++) {
contour1D.push_back( contour2D[border][p] );
}
}
//limiting contours size to reduce distance comparison time
contour1D.resize( 300 );
return contour1D;
}
int main()
{
string path = "./images/";
cv::Ptr <cv::ShapeContextDistanceExtractor> distanceExtractor = cv::createShapeContextDistanceExtractor();
//base image
Mat baseImage= imread( path + "1.png", IMREAD_GRAYSCALE);
vector<Point> baseImageContours= findContours( baseImage );
for ( int idx = 2; idx <= MAX_SHAPES; ++idx ) {
stringstream imgName;
imgName << path << idx << ".png";
Mat compareToImg=imread( imgName.str(), IMREAD_GRAYSCALE ) ;
vector<Point> contii = findContours( compareToImg );
float distance = distanceExtractor->computeDistance( baseImageContours, contii );
std::cout<<" distance to " << idx << " : " << distance << std::endl;
}
return 0;
}
Result
distance to 2 : 89.7951
distance to 3 : 14.6793
distance to 4 : 6.0063
distance to 5 : 4.79834
distance to 6 : 0.0963184
distance to 7 : 0.00212693
Do three things: 1. Forget about image comparison since you really comparing stroke symbols. 2. Download and play wth a Gesture Search app from google store; 3. Realize that for good performance you cannot recognize your strokes without using timestamp information about stroke drawing. Otherwice we would have a successful handwriting recognition. Then you can research Android stroke reco library to write your code properly.
I want to mutiply 2 with each element of vec3 in opencv as we do in Matlab simplt by ".*". I searched alot but didn't find any command is their any command for this or not in opencv? thanks in advance for any help.
This answer would suggest you can just use the * assignment operator in C++.
If you are using Java I don't think this is possible, you can only multiply a Mat by another Mat.
So you would need to create a new Mat instance of the same size and type, initialised with the scalar value you want to multiply by.
You can easily create a funcion to do this:
public Mat multiplyScalar(Mat m, double i)
{
return m = m.mul(new Mat((int)m.size().height, (int)m.size().width, m.type(), new Scalar(i)));
}
Then x = multiplyScalar(x, 5); will multiply each element by 5.
I am new to opencv, so please help me in solving this basic query. I am trying to find the max. value of a Mat variable. I tried to use the max_element and minMaxLoc, but end up facing errors, as the function keeps saying the datatype matched is wrong. I checked it over and over again, but am not successful. here is my code.
ABS_DST is the MAT variable
double *estimate,*min;
CvPoint *minLoc,*maxLoc;
Size s = abs_dst.size();
int rows = s.height;
int cols = s.width;
double imagearray[rows][cols] = abs_dst.data();
minMaxLoc(imagearray,min,estimate,minLoc,maxLoc);
I even tried giving the Mat variable abs_dst directly. But have not succeeded. there's an optional input mask array, which I have ignored as I do not require that.
Do next:
Point[] Mat_To_Point = Your_Mat_Variable.toArray();
And next you can to sort your array
I think I got the answer. Thanks for your efforts. The problem is minMaxLoc doesn't take RGB images array, as it is 3 channel. I had to convert the ABS_DST to Gray scale.
Secondly,
it is not
CvPoint *minLoc,maxLoc;
it is
Point *minLoc,*maxLoc;
I need not convert it to array, as converting to Gray Scale will directly give me a 1D channel, enough for the minMaxLoc. My apologies for my own mistakes and thanks once again for your efforts.
This question already has answers here:
Closed 11 years ago.
Possible Duplicate:
OpenCV rgb value for cv::Point in cv::Mat
As you know, in matlab it's easy to get r/g/b values using r = image(:,:,1).
But in openCV (before 2.2) we must use pointer like this:
plImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 0]=111; // B
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 1]=112; // G
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 2]=113; // R
But as openCV2.3 comes out, it's easy to get pixel value of a single channel image like this:
Mat image;
int pixel = image.at<uchar>(row,col);
So I just wonder it there also a easy way to get the r,g,b pixel value of a multichannel image just like that in the Matlab? Any help will be appreciated =)
For C++ interface you can do:
Vec3f pixel = image.at<Vec3f>(row, col);
int b = pixel[0];
int g = pixel[1];
int r = pixel[2];
as vasile said, getting a cell as a Vec3 will get you the pixel with easy access to its rgb components, this is the simplest solution in opencv since the data structure saves the pixels in the following format "RGBRGBRGBRGBRGB..." while matlab saves it as "RRRRRRRGGGGGGGBBBBBBBB..."
to get a specified channel like in matlab you can use the CvSplit (or cv::split in c++ style), this function will split the image into its 3-4 different channels so you could access a channels like in matlab. in the provided links you can find also a reference for the opposite function - merge