SUSAN corner detector. More...

Functions

AFAPI features susan (const array &in, const unsigned radius=3, const float diff_thr=32.0f, const float geom_thr=10.0f, const float feature_ratio=0.05f, const unsigned edge=3)
 C++ Interface for SUSAN corner detector. More...
 
AFAPI af_err af_susan (af_features *out, const af_array in, const unsigned radius, const float diff_thr, const float geom_thr, const float feature_ratio, const unsigned edge)
 C Interface for SUSAN corner detector. More...
 

Detailed Description

SUSAN corner detector.

SUSAN is an acronym standing for Smallest Univalue Segment Assimilating Nucleus. This method places a circular disc over the pixel to be tested (a.k.a nucleus) to compute the corner measure of that corresponding pixel. The region covered by the circular disc is M, and a pixel in this region is represented by \(\vec{m} \in M\) where \(\vec{m}_0\) is the nucleus. Every pixel in the region is compared to the nucleus using the following comparison function:

\( c(\vec{m}) = e^{-{(({I(\vec{m}) - I(\vec{m}_0))} / t})^6}\)

where t is radius of the region, I is the brightness of the pixel.

Response of SUSAN operator is given by the following equation:

\( R(M) = \begin{cases} g - n(M) \quad \text{if } n(M) < g\\ 0 \quad \text{otherwise},\\ \end{cases}\)

where \( n(M) = \sum\nolimits_{\vec{m} \in M} c(\vec{m})\), g is named the geometric threshold and n is the number of pixels in the mask which are within t of the nucleus.

Importance of the parameters, t and g is explained below:


Function Documentation

◆ af_susan()

AFAPI af_err af_susan ( af_features out,
const af_array  in,
const unsigned  radius,
const float  diff_thr,
const float  geom_thr,
const float  feature_ratio,
const unsigned  edge 
)

C Interface for SUSAN corner detector.

Parameters
[out]outis af_features struct composed of arrays for x and y coordinates, score, orientation and size of selected features
[in]inis input grayscale/intensity image
[in]radiusnucleus radius for each pixel neighborhood
[in]diff_thrintensity difference threshold a.k.a t from equations in description
[in]geom_thrgeometric threshold
[in]feature_ratiois maximum number of features that will be returned by the function
[in]edgeindicates how many pixels width area should be skipped for corner detection
Returns
AF_SUCCESS if SUSAN corner detection is successfull, otherwise an appropriate error code is returned.
Note
If in is a 3d array, a batch operation will be performed.

◆ susan()

AFAPI features af::susan ( const array in,
const unsigned  radius = 3,
const float  diff_thr = 32.0f,
const float  geom_thr = 10.0f,
const float  feature_ratio = 0.05f,
const unsigned  edge = 3 
)

C++ Interface for SUSAN corner detector.

Parameters
[in]inis input grayscale/intensity image
[in]radiusnucleus radius for each pixel neighborhood
[in]diff_thrintensity difference threshold
[in]geom_thrgeometric threshold a.k.a t from equations in description
[in]feature_ratiois maximum number of features that will be returned by the function
[in]edgeindicates how many pixels width area should be skipped for corner detection
Returns
If SUSAN corner detection is successfull returns an object of Features class, composed of arrays for x and y coordinates, score, orientation and size of selected features, otherwise exception is thrown.
Note
If in is a 3d array, a batch operation will be performed.
Examples
computer_vision/susan.cpp.