binarydescriptor

A binary descriptor is a type of feature descriptor used in computer vision and image processing. Its primary function is to represent the local characteristics of an image region in a compact binary string. Unlike intensity-based descriptors that store raw pixel values or gradients, binary descriptors encode information in a series of binary tests.

The creation of a binary descriptor typically involves a set of carefully chosen sampling points within a neighborhood. These points are then compared against each other, or against a reference point, to determine the outcome of a binary test. For instance, a common test might be whether the intensity of one pixel is greater than the intensity of another. The results of these tests are then concatenated to form a binary string. This binary string is the descriptor.

The advantage of binary descriptors lies in their efficiency. The binary representation allows for very fast matching using bitwise operations, such as the Hamming distance, which counts the number of differing bits between two descriptors. This makes them highly suitable for real-time applications like object recognition and image retrieval where large numbers of features need to be compared quickly. Examples of popular binary descriptors include BRIEF (Binary Robust Independent Elementary Features), ORB (Oriented FAST and Rotated BRIEF), and BRISK (Binary Robust Invariant Scalable Keypoints). These descriptors differ in how they select sampling points and perform the binary tests, leading to variations in their robustness to image transformations like rotation, scaling, and illumination changes.