- Source: GLOH
GLOH (Gradient Location and Orientation Histogram) is a robust image descriptor that can be used in computer vision tasks. It is a SIFT-like descriptor that considers more spatial regions for the histograms. An intermediate vector is computed from 17 location and 16 orientation bins, for a total of 272-dimensions. Principal components analysis (PCA) is then used to reduce the vector size to 128 (same size as SIFT descriptor vector).
See also
Scale-invariant feature transform
Speeded Up Robust Features
LESH – Local Energy-based Shape Histogram
Feature detection (computer vision)
References
Krystian Mikolajczyk and Cordelia Schmid "A performance evaluation of local descriptors", IEEE Transactions on Pattern Analysis and Machine Intelligence, 10, 27, pp 1615--1630, 2005.
Kata Kunci Pencarian:
- GLOH
- Scale-invariant feature transform
- Circle Hough Transform
- Hough transform
- Histogram of oriented gradients
- Sobel operator
- Edge detection
- Pyramid (image processing)
- Blob detection
- Speeded up robust features
