# Revision history [back]

### Looking for ways to speed up pixel scanning

So I am trying to implement a pixel scanner, where I go through every pixel and check if it is white (the image has already been threshold-ed at this point) and if it is white get the pixel's respective x and y coordinate which I use to calculate distances. So far I have been doing it the double for-loop way, and it is adding significant slowdowns compared to the rest of my pipeline. I would like to speed this up. I have looked into using cv::findNonZero(), it gives me a vector of cv::Point, when I try and access the vector at some interation like vec[ i ] the output is [ rowValue, colValue ] which is expected but I don't know how to access the "rowValue" or "colValue" independently that I need in order to calculate distances. I have heard about using cv::LUT() but I'm having some trouble understanding how to use it. Thanks is advanced and let me know if more info is needed. Code below:

   cv::Mat W; // approx 1000 x 1000
for (int i = 0; i < W.cols; i++)
{
for (int j = 0; j < W.rows; j++)
{
cv::Scalar pixelColor = counter.at<uchar>(j, i);
if (pixelColor.val[0] == 255)
{
// pixelLocations are defined as a ROS message, A B C D are constants used to
// calculate distances in meters
pixelLocation.x = (A * i) + B; // distance in x direction relative to robot
pixelLocation.y = (C * j) + D; // distance in front of robot
}
}
}


### Looking for ways to speed up pixel scanning

So I am trying to implement a pixel scanner, where I go through every pixel and check if it is white (the image has already been threshold-ed at this point) and if it is white get the pixel's respective x and y coordinate which I use to calculate distances. So far I have been doing it the double for-loop way, and it is adding significant slowdowns compared to the rest of my pipeline. I would like to speed this up. I have looked into using cv::findNonZero(), it gives me a vector of cv::Point, when I try and access the vector at some interation like vec[ i ] the output is [ rowValue, colValue ] which is expected but I don't know how to access the "rowValue" or "colValue" independently that I need in order to calculate distances. I have heard about using cv::LUT() but I'm having some trouble understanding how to use it. Thanks is advanced and let me know if more info is needed. Code below:

   cv::Mat W; // approx 1000 x 1000
for (int i = 0; i < W.cols; i++)
{
for (int j = 0; j < W.rows; j++)
{
cv::Scalar pixelColor = counter.at<uchar>(j, i);
if (pixelColor.val[0] == 255)
{
// pixelLocations are defined as a ROS message, A B C D are constants constants
// used to
// calculate distances in meters
pixelLocation.x = (A * i) + B; // distance in x direction relative to robot
pixelLocation.y = (C * j) + D; // distance in front of robot
}
}
}

 3 None berak 32993 ●7 ●81 ●312

### Looking for ways to speed up pixel scanning

So I am trying to implement a pixel scanner, where I go through every pixel and check if it is white (the image has already been threshold-ed at this point) and if it is white get the pixel's respective x and y coordinate which I use to calculate distances. So far I have been doing it the double for-loop way, and it is adding significant slowdowns compared to the rest of my pipeline. I would like to speed this up. I have looked into using cv::findNonZero(), it gives me a vector of cv::Point, when I try and access the vector at some interation like vec[ i ] the output is [ rowValue, colValue ] which is expected but I don't know how to access the "rowValue" or "colValue" independently that I need in order to calculate distances. I have heard about using cv::LUT() but I'm having some trouble understanding how to use it. Thanks is advanced and let me know if more info is needed. Code below:

   cv::Mat W; // approx 1000 x 1000
for (int i = 0; i < W.cols; i++)
{
for (int j = 0; j < W.rows; j++)
{
cv::Scalar pixelColor = counter.at<uchar>(j, i);
if (pixelColor.val[0] == 255)
{
// pixelLocations are defined as a ROS message, A B C D are constants
// used to calculate distances in meters
pixelLocation.x = (A * i) + B; // distance in x direction relative to robot
pixelLocation.y = (C * j) + D; // distance in front of robot
}
}
}