SURF feature extractor and descriptor

1. What is surf feature extraction?
2. What is feature descriptor in image processing?
3. What's the difference between SIFT and SURF?

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.

What is feature descriptor in image processing?

A feature descriptor is a method that extracts the feature descriptions for an interest point (or the full image). Feature descriptors serve as a kind of numerical “fingerprint” that we can use to distinguish one feature from another by encoding interesting information into a string of numbers.

What's 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.