| Feature detection |
|---|
|
Output of a typical corner detection algorithm
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| Edge detection |
| Canny · Canny-Deriche · Differential · Sobel · Prewitt · Roberts Cross |
| Interest point detection |
| Corner detection |
| Harris operator · Shi and Tomasi · Level curve curvature · SUSAN · FAST |
| Blob detection |
| Laplacian of Gaussian (LoG) · Difference of Gaussians (DoG) · Determinant of Hessian (DoH) · Maximally stable extremal regions · PCBR |
| Ridge detection |
| Hough transform |
| Structure tensor |
| Affine invariant feature detection |
| Affine shape adaptation · Harris affine · Hessian affine |
| Feature description |
| SIFT · SURF · GLOH · HOG · LESH |
| Scale-space |
| Scale-space axioms · Implementation details · Pyramids |
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).