I was asked to recognize logo in an image using opencv. The lecturer told me that I don't have to do logo detection but logo recognition only. I am using opencv in c++. Can I know the easiest way to do it??
Ps: newbie in computer vision.
C++ – How to Perform Logo Recognition with OpenCV
c++computer-visionimage-recognitionopencv
Related Solutions
You may want to go with SIFT using Rob Hess' SIFT Library. It's using OpenCV and also pretty fast. I guess that easier than your current way of approaching the logo detection :)
Try also looking for SURF, which claims to be faster & robuster than SIFT. This Feature Detection tutorial will help you.
An alternative approach would be to extract features (keypoints) using the scale-invariant feature transform (SIFT) or Speeded Up Robust Features (SURF).
You can find a nice OpenCV code example in Java, C++, and Python on this page: Features2D + Homography to find a known object
Both algorithms are invariant to scaling and rotation. Since they work with features, you can also handle occlusion (as long as enough keypoints are visible).
Image source: tutorial example
The processing takes a few hundred ms for SIFT, SURF is bit faster, but it not suitable for real-time applications. ORB uses FAST which is weaker regarding rotation invariance.
Best Answer
It largely depends on your kind of images.
Assuming that you have a single complete rigid logo to find, the simplest thing to try is template matching.
A more accurate approach is to match descriptors. You can also see a related topic on SO here
Other more robust approaches would require to build constellations of keypoints on your reference logo, and match those constellations on the target image.
Last, but not least, have fun on Google!