OpenCV SURF

1. What is SURF in OpenCV?
2. What is the difference between SIFT and SURF?
3. How do you use SURF algorithm?
4. What is SURF feature extraction?

What is SURF in OpenCV?

SURF in OpenCV. OpenCV provides SURF functionalities just like SIFT. You initiate a SURF object with some optional conditions like 64/128-dim descriptors, Upright/Normal SURF etc. All the details are well explained in docs. Then as we did in SIFT, we can use SURF.

What is the difference between SIFT and SURF?

SIFT is an algorithm used to extract the features from the images. SURF is an efficient algorithm is same as SIFT performance and reduced in computational complexity. SIFT algorithm presents its ability in most of the situation but still its performance is slow.

How do you use SURF algorithm?

The steps of SURF algorithm contain three sections: interest points detecting, interest points describing and interest points matching. Interest points detecting uses a detector based on Hessian matrix, its stability and repeatability outperforms the existing state-of-the-art, e.g. a detector based on Harris.

What is SURF feature extraction?

In computer vision, speeded up robust features (SURF) is a patented local feature detector and descriptor. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction. It is partly inspired by the scale-invariant feature transform (SIFT) descriptor.