Blob Detection (Feature Detection)
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Description
The regions or points which have noticeable difference with their surroundings is called blob. Blob detection is the problem of detecting such blobs in a given image.
Related Problems
Related: Corner Detection
Parameters
No parameters found.
Table of Algorithms
| Name | Year | Time | Space | Approximation Factor | Model | Reference |
|---|---|---|---|---|---|---|
| T. Lindeberg DoG | 2012 | $O(n^{2})$ | Deterministic | |||
| T. Lindeberg DoG | 2015 | $O(n \log n)$ | Deterministic | |||
| SIFT Algorithm Lowe | 2004 | $O(n^{3})$ | Deterministic | |||
| Hessain Determinant Lindeberg | 1994 | $O(n^{3})$ | Deterministic | |||
| Hessain Determinant Lindeberg | 1998 | $O(n^{3})$ | Deterministic | |||
| SURF Descriptor | 2006 | $O(n^{2})$ | Deterministic | |||
| Hessian-Laplace Mikolajczyk and Schmid | 2004 | $O(n^{3})$ | Deterministic | |||
| Spatio-temporal Geert Willems; Tinne Tuytelaars and Luc van Gool () | 2008 | $O(n^{2})$ | Deterministic | |||
| Lindeberg's watershed-based grey-level blob detection algorithm | 1991 | $O(n^{3})$ | Deterministic | |||
| Maximally stable extremal regions Matas | 2002 | $O(n^{2} log^{3} n)$ | Deterministic | |||
| A. Baumberg. | 2000 | $O(n^{3})$ | Deterministic | |||
| Y. Dufournaud; C. Schmid; and R. Horaud | 2000 | $O(n^{2} \log\log n)$ | Deterministic | |||
| local scale-invariant Lowe | 1999 | $O(n^{3})$ | Deterministic | |||
| T. Tuytelaars and L. Van Gool | 2000 | $O(n^{3})$ | Deterministic |