Laser line detection using OpenCV - c++

Question

I'm working on a project in which I need to detect a red laser line in an image. This is the strategy I have in mind.
Separate the R, G, B channels in the image.
Threshold the images at a high intensity value.
Using the 3 binary images generated, perform the element wise operation r && !g && !b. (&& is logical AND, ! is logical NOT).
The resulting matrix is a binary image with 1 on the regions where the laser was present.
This worked with a few test images on Matlab. But my problem is that this needs to be implemented using OpenCV in C/ C++.
I've tried going through most of the library functions, but there seems no intuitive/ simple way of working with binary images and performing logical operations on them.
Can someone please point me to the OpenCV functions/ methods that you think I might find useful? I've figured that cvThresholdImage can be used for thresholding, but that's pretty much about it.

Answer 1

So you already figured out steps 1 and 2 in openCV then? If you are just trying to use the logical operators, openCV gives you access to the raw data which you can then operate on with logical operators. Assuming you have already split into three channels and thresholded
//three binary images in the format you specified above
cv::Mat g;
cv::Mat b;
cv::Mat r;
uchar* gptr = g.data();
uchar* bptr = b.data();
uchar* rptr = r.data();
//assuming the matrix data is continuous you can just iterate straight through the data
if(g.isContinuous()&&r.isContinuous()&&b.isContinuous())
{
for(int i = 0; i < g.rows*g.cols; i++)
{
rptr[i] = rptr[i]&&!bptr[i]&&!gptr[i];
}
}
r now contains the output you described. You could also copy it into a new matrix if you don't want to overwrite r.
There are several ways of iterating through a cv::Mat and accessing all the data points and C++ provides all the logical operators you could want. To my knowledge openCV does not provide matrix logical operator functions but you could write your own very easily as shown above.
Edit
As suggested by QuentinGeissmann you could accomplish the same thing using the bitwise_not and bitwise_and functions. I was not aware that they existed. I suspect that using them would be slower because of the number of times the data must be iterated through but it could be done in less code.
cv::bitwise_not(g,g);
cv::bitwise_not(b,b);
cv::bitwise_and(b,g,b);
cv::bitwise_and(r,b,r);
//r now contains r&&!b&&!g