ORB descriptor

1. What is an ORB descriptor?
2. What is ORB in image processing?
3. Is ORB better than SIFT?
4. What is ORB in Python?
5. How does ORB work in Opencv?

What is an ORB descriptor?

The ORB (Oriented Fast and Rotated Brief) descriptor is a somewhat similar to BRIEF . It doesn't have an elaborate sampling pattern as BRISK or FREAK . However, there are two main differences between ORB and BRIEF: ORB uses an orientation compensation mechanism, making it rotation invariant.

What is ORB in image processing?

Oriented FAST and Rotated BRIEF (ORB) algorithm is one of feature detector and descriptor that is widely used in image stitching and registration systems such as simultaneous localization and mapping (SLAM) systems. ORB algorithm has improved the speed of processing and robustness.

Is ORB better than SIFT?

We showed that ORB is the fastest algorithm while SIFT performs the best in the most scenarios. For special case when the angle of rotation is proportional to 90 degrees, ORB and SURF outperforms SIFT and in the noisy images, ORB and SIFT show almost similar performances.

What is ORB in Python?

ORB is a fusion of FAST keypoint detector and BRIEF descriptor with some added features to improve the performance. FAST is Features from Accelerated Segment Test used to detect features from the provided image. It also uses a pyramid to produce multiscale-features.

How does ORB work in Opencv?

ORB is basically a fusion of FAST keypoint detector and BRIEF descriptor with many modifications to enhance the performance. First it use FAST to find keypoints, then apply Harris corner measure to find top N points among them. It also use pyramid to produce multiscale-features.