Howtosignalprocessing
The detector is a corner detector. The descriptor is a binary string representing the signs of the difference between certain pairs of pixels around the interest point.
- What is the difference between detector and descriptor?
- What is a feature descriptor?
- What is feature detection and description?
- What are feature detectors used for?
What is the difference between detector and descriptor?
Feature detectors are used to find the essential features from the given image, whereas descriptors are used to describe the extracted features. Moravec introduced an interest operator based on intensity variations in 1980 [72]. But it was not scale invariant and rotation invariant. It was sensitive to noise too.
What is a feature descriptor?
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 is feature detection and description?
Feature detection is a method to compute abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. Feature detection is a low-level image processing operation.
What are feature detectors used for?
Feature detectors are also thought to play an important role in speech perception, where their function would be to detect those binary features that distinguish one phoneme from another. Also called feature analyzer.
