Speed up OpenCV - c++

Question

I am using OpenCV 2.4 (C++) for line finding on grayscale images. This involves some basic image processing steps like blurring, threshold, Canny edge detector, gradient filter or Hough transformation. I have to apply the line finding algorithm on thousands of images.
Is there a way to speed up the calculation considering the large number of images?
Does one of the following provide help? Intel TBB, IPP or OpenCV GPU?
I heard that OpenCV GPU can speed up calculations but data transfer is slowly. So using GPU might not be the right choice here?
Thank You!
EDIT:
Is there any sense in using parallel_for from TBB to speed up image processing? If I use a for loop like this:
for(int i=0; i<image_location.size();++i)
{
Mat img=imread(image_location[i]);
blur(img...);
threshold(img...);
...
}
Can I improve performance by using parallel_for instead? Can anyone provide examples how to use parallel_for including some opencv operations?

Answer 1

The scope of your question is virtually unbounded.
First of all, have you measured the performance of your application to detect the actual bottleneck(s) ? My guess would be the Hough transform, but who knows what else your code is doing. Now, if the Hough transform is the slow piece, and supposing OpenCV has a fast implementation of it, then this is the reason I tell you the question is problematic. Changing for a somewhat better implementation doesn't help much when you decide to increase your already large number of images, the problem is in the approach itself.
Do you really need to use Hough ? Maybe you could achieve something similar/better using morphological operators ? Are the images from some common domain ? Can you include examples of them ? Etc, etc.