I want to create a 1D plot from an image. Then I want to determine the maxima and their distances to each other in c++.
I am looking for some tips on how I could approach this.
I load the image as cv::Mat. In opencv I have searched, but only found the histogram function, which is wrong. I want to get a cross section of the image - from left to right.
does anyone have an idea ?
Well I have the following picture:
From this I want to create a 1D plot like in the following picture (I created the plot in ImageJ).
Here you can see the maxima (I could refine it with "smooth").
I want to determine the positions of these maxima and then the distances between them.
I have to get to the 1D plot somehow. I suppose I can get to the maxima with a derivation?
++++++++++ UPDATE ++++++++++
Now i wrote this to get an 1D Plot:
cv::Mat img= cv::imread(imgFile.toStdString(), cv::IMREAD_ANYDEPTH | cv::IMREAD_COLOR);
cv::cvtColor(img, img, cv::COLOR_BGR2GRAY);
uint8_t* data = img.data;
int width = img.cols;
int height = img.rows;
int stride = img.step;
std::vector<double> vPlot(width, 0);
for (int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
uint8_t val = data[ i * stride + j];
vPlot[j]=vPlot[j] + val;
}
}
std::ofstream file;
file.open("path\\plot.csv");
for(int i = 0; i < vPlot.size(); i++){
file << vPlot[i];
file << ";";
}
file.close();
When i plot this in excel i got this:
Thats looks not so smooth as in ImageJ. Did i something wrong?
I need it like in the Plot of ImageJ - more smooth.
ok I got it:
for (int i = 0; i < vPlot.size(); i++) {
vPlot[i] = vPlot[i] / height;
}
Ok but i don't know how to get the maxima an distances.
When i have the local maxima (i don't know how), i can calculate the distance between them with the index of the vetcor elements.
Has anybody an idea to get the local Maxima out of the vector, that I plot above ?
Now o wrote this to find the maxima:
// find maxima
std::vector<int> idxMax;
int flag = 0;
for(int i = 1; i < avg.size(); i++){
double diff = avg[i] - avg[i-1];
if(diff < 0){
if(flag>0){
idxMax.push_back(i);
flag = -1;
}
}
if(diff >= 0){
if(flag<=0){
flag = 1;
}
}
}
But more maxima are found than wanted. The length of the vector varies and also the number of peaks. These can be close together or far away. They are also not always the same height, as can be seen in the picture
In Python I normally use functions like vstack, stack, etc to easily create a 3D array by stacking 2D arrays one onto another.
Is there any way to do this in C++?
In particular, I have loaded a image into a Mat variable with OpenCV like:
cv::Mat im = cv::imread("image.png", 0);
I would like to make a 3D array/Mat of N layers by stacking copies of that Mat variable.
EDIT: This new 3D matrix has to be "travellable" by adding an integer to any of its components, such that if I am in the position (x1,y1,1) and I add +1 to the last component, I arrive to (x1,y1,2). Similarly for any of the coordinates/components of the 3D matrix.
SOLVED: Both answers from #Aram and #Nejc do exactly what expected. I set #Nejc 's answer as the correct one for his shorter code.
The Numpy function vstack returns a contiguous array. Any C++ solution that produces vectors or arrays of cv::Mat objects does not reflect the behaviour of vstack in this regard, becase separate "layers" belonging to individual cv::Mat objects will not be stored in contiguous buffer (unless a careful allocation of underlying buffers is done in advance of course).
I present the solution that copies all arrays into a three-dimensional cv::Mat object with a contiguous buffer. As far as the idea goes, this answer is similar to Aram's answer. But instead of assigning pixel values one by one, I take advantage of OpenCV functions. At the beginning I allocate the matrix which has a size N X ROWS X COLS, where N is the number of 2D images I want to "stack" and ROWS x COLS are dimensions of each of these images.
Then I make N steps. On every step, I obtain the pointer to the location of the first element along the "outer" dimension. I pass that pointer to the constructor of temporary Mat object that acts as a kind of wrapper around the memory chunk of size ROWS x COLS (but no copies are made) that begins at the address that is pointed-at by pointer. I then use copyTo method to copy i-th image into that memory chunk. Code for N = 2:
cv::Mat img0 = cv::imread("image0.png", CV_IMREAD_GRAYSCALE);
cv::Mat img1 = cv::imread("image1.png", CV_IMREAD_GRAYSCALE);
cv::Mat images[2] = {img0, img1}; // you can also use vector or some other container
int dims[3] = { 2, img0.rows, img0.cols }; // dimensions of new image
cv::Mat joined(3, dims, CV_8U); // same element type (CV_8U) as input images
for(int i = 0; i < 2; ++i)
{
uint8_t* ptr = &joined.at<uint8_t>(i, 0, 0); // pointer to first element of slice i
cv::Mat destination(img0.rows, img0.cols, CV_8U, (void*)ptr); // no data copy, see documentation
images[i].copyTo(destination);
}
This answer is in response to the question above of:
In Python I normally use functions like vstack, stack, etc to easily create a 3D array by stacking 2D arrays one onto another.
This is certainly possible, you can add matrices into a vector which would be your "stack"
For instance you could use a
std::vector<cv::Mat>>
This would give you a vector of mats, which would be one slice, and then you could "layer" those by adding more slices vector
If you then want to have multiple stacks you can add that vector into another vector:
std::vector<std::vector<cv::Mat>>
To add matrix to an array you do:
myVector.push_back(matrix);
Edit for question below
In such case, could I travel from one position (x1, y1, z1) to an immediately upper position doing (x1,y1,z1+1), such that my new position in the matrix would be (x1,y1,z2)?
You'll end up with something that looks a lot like this. If you have a matrix at element 1 in your vector, it doesn't really have any relationship to the element[2] except for the fact that you have added it into that point. If you want to build relationships then you will need to code that in yourself.
You can actually create a 3D or ND mat with opencv, you need to use the constructor that takes the dimensions as input. Then copy each matrix into (this case) the 3D array
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
int main() {
// Dimensions for the constructor... set dims[0..2] to what you want
int dims[] = {5, 5, 5}; // 5x5x5 3d mat
Mat m = Mat::zeros(5, 5, CV_8UC1);
for (size_t i = 0; i < 5; i++) {
for (size_t k = 0; k < 5; k++) {
m.at<uchar>(i, k) = i + k;
}
}
// Mat with constructor specifying 3 dimensions with dimensions sizes in dims.
Mat 3DMat = Mat(3, dims, CV_8UC1);
// We fill our 3d mat.
for (size_t i = 0; i < m2.size[0]; i++) {
for (size_t k = 0; k < m2.size[1]; k++) {
for (size_t j = 0; j < m2.size[2]; j++) {
3DMat.at<uchar>(i, k, j) = m.at<uchar>(k, j);
}
}
}
// We print it to show the 5x5x5 array.
for (size_t i = 0; i < m2.size[0]; i++) {
for (size_t k = 0; k < m2.size[1]; k++) {
for (size_t j = 0; j < m2.size[2]; j++) {
std::cout << (int) 3DMat.at<uchar>(i, k, j) << " ";
}
std::cout << endl;
}
std::cout << endl;
}
return 0;
}
Based on the question and comments, I think you are looking for something like this:
std::vector<cv::Mat> vec_im;
//In side for loop:
vec_im.push_back(im);
Then, you can access it by:
Scalar intensity_1 = vec_im[z1].at<uchar>(y, x);
Scalar intensity_2 = vec_im[z2].at<uchar>(y, x);
This assumes that the image is single channel.
I have a questions about a for loop and its return value. This is C++ code, and I'm using openCV 2.4V.
Input to this function is max value of 600 images with pooling.
600 images << pooling << max value points.
The size of "res" matrix is 600x128 and vec.size() = 600.
For me, within the for loop, the res never get updated, however return value is not zeros.
I suspected
"ptmat.copyTo(subView)"
because, I thought that is not necessary line. However when I took that out, res did not get updated(being zero like initial Mat). Can anybody explain how does the res value get updated?
Also why does this function is called concatenate..?
Mat
concatenateMat(vector<vector<Mat> > &vec) {
int subFeatures = vec[0][0].rows * vec[0][0].cols;
int height = vec[0].size() * subFeatures;
int width = vec.size();
Mat res = Mat::zeros(height, width, CV_64FC1);
for (int i = 0; i<vec.size(); i++) {
for (int j = 0; j<vec[i].size(); j++) {
Rect roi = Rect(i, j * subFeatures, 1, subFeatures);
Mat subView = res(roi);
Mat ptmat = vec[i][j].reshape(0, subFeatures);
ptmat.copyTo(subView);
}
}
return res;
}
According to OpenCV documentation, the Mat::operator() does not make a copy of matrix data, thus any change to subView matrix object in the loop will be reflected in res matrix object as well. That's the line you've mentioned:
ptmat.copyTo(subView);
It's called concatenate because it concatenates 2D vector of Mat objects into a single one.
I want to segment car plate to get separate characters.
I found some article, where such segmentation performed using brightness histograms (as i understand - sum of all non-zero pixels).
How can i calculate such histogram? I would really appreciate for any help!
std::vector<int> computeColumnHistogram(const cv::Mat& in) {
std::vector<int> histogram(in.cols,0); //Create a zeroed histogram of the necessary size
for (int y = 0; y < in.rows; y++) {
p_row = in.ptr(y); ///Get a pointer to the y-th row of the image
for (int x = 0; x < in.cols; x++)
histogram[x] += p_row[x]; ///Update histogram value for this image column
}
//Normalize if you want (you'll get the average value per column):
// for (int x = 0; x < in.cols; x++)
// histogram[x] /= in.rows;
return histogram;
}
Or use reduce as suggested by Berak, either calling
cv::reduce(in, out, 0, CV_REDUCE_AVG);
or
cv::reduce(in, out, 0, CV_REDUCE_SUM, CV_32S);
out is a cv::Mat, and it will have a single row.
I'm new to OpenCV a have some trouble regarding writing to a subrange of a Mat-Object.
The code below iterates a given Image. For each pixel, it takes pixel within a range of 5x5, finds the brightest pixel, and put all other pixel to 0.
I call the function multiple times. After a random number of calls the function gives me a segmentation fault or "malloc memory corruption". Sometimes I can call the function 10 times with no problems sometimes only twice, then the program stops.
I tracked down the problem to the line, where I write to the original image using the subimage.
subimage.at<uchar>(rowSubimage,colSubimage) = 0;
There is the function that drives me crazy:
void findMaxAndBlackout(Mat& image, int size){
Point centralPoint;
Size rangeSize = Size(size,size);
Mat subimage;
Rect range;
// iterate the image
for(int row = 0; row <= image.rows-size; row++){
for(int col = 0; col <= image.cols-size; col++){
centralPoint = Point(col,row);
range = Rect(centralPoint, rangeSize);
// slice submatrix and find max
subimage = image(range);
double max;
minMaxLoc( subimage, NULL, &max, NULL, NULL );
// iterate the surrounding
for(int rowSubimage = 0; rowSubimage <= subimage.rows; rowSubimage++){
for(int colSubimage = 0; colSubimage <= subimage.cols; colSubimage++){
if(subimage.at<uchar>(rowSubimage,colSubimage) < max){
//this line cause the trouble
subimage.at<uchar>(rowSubimage,colSubimage) = 0;
}
}
}
}
}}
The Mat-Object is generated using:
Mat houghImage = imread("small_schachbrett1_cam.png", CV_LOAD_IMAGE_GRAYSCALE);
Please help me understand the problem.
If you know a better or more efficient way to achieve the same result please let me know. I am open for any improvements
Regards
benniz
You are out of range:
row <= image.rows-size
col <= image.cols-size
rowSubimage <= subimage.rows
colSubimage <= subimage.cols
should be
row < image.rows-size
col < image.cols-size
rowSubimage < subimage.rows
colSubimage < subimage.cols