| Feature detection | |
|---|---|
 Output of a typical corner detection algorithm |
|
| Edge detection | |
| Canny | |
| Canny-Deriche | |
| Differential | |
| Sobel | |
| 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 | |
| Ridge detection | |
| Affine invariant feature detection | |
| Affine shape adaptation | |
| Harris affine | |
| Hessian affine | |
| Feature description | |
| SIFT | |
| SURF | |
| GLOH | |
| LESH | |
| Scale-space | |
| Scale-space axioms | |
| Implementation details | |
| Pyramids | |
SURF (Speeded Up Robust Features) is a robust image detector & descriptor, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images. As basic image features it uses a Haar wavelet approximation of the determinant of Hessian blob detector.
Contents |
Implementations
- Original implementation (closed source)
- OpenSURF (open source) implementation with detailed documentation and reference paper (C++, C#, Linux)
- OpenCV SURF (open source) implementation of SURF feature extraction (OpenCV 2.0)
- GPU SURF (closed source) a GPU Implementation
- libmv SURF (open source) implementation of extraction and matching.
- Dlib C++ Library (open source) implementation of SURF feature extraction
- Pan-o-matic (open source) software which includes an implementation of the SURF algorithm
- C# SURF plugin for Multi-Agent Serving System (open source) implementation of extraction and matching.
- JavaSurf (open source) java implementation (platform independent)
- ImageJ SURF (open source) SURF implementation as ImageJ plugin with a convenient GUI and output of statistics (platform independent).
See also
- Scale-invariant feature transform
- Gradient Location and Orientation Histogram
- LESH - Local Energy based Shape Histogram
- Blob detection
- Feature detection (computer vision)
References
- Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool "SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359, 2008
- Christopher Evans "Notes on the OpenSURF Library", MSc Computer Science, University of Bristol
External links
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