GLOH
From Wikipedia, the free encyclopedia
| Feature detection |
|---|
 Output of a typical corner detection algorithm |
| Edge detection |
|
| Corner detection |
|
| Blob detection |
|
| Ridge detection |
| Hough transform |
| Structure tensor |
| Affine invariant feature detection |
|
| Feature description |
| Scale space |
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. The higher dimensionality of the descriptor is reduced to 64 through principal components analysis (PCA).
See also
- Scale-invariant feature transform
- Speeded Up Robust Features
- LESH - Local Energy based Shape Histogram
- Feature detection (computer vision)
References
This article is issued from Wikipedia. The text is available under the Creative Commons Attribution/Share Alike; additional terms may apply for the media files.