Detailed Description

Computes the corners in an image using a method based upon FAST9 algorithm suggested in [3] and with some updates from [4] with modifications described below.

It extracts corners by evaluating pixels on the Bresenham circle around a candidate point. If \( N \) contiguous pixels are brighter than the candidate point by at least a threshold value \( t \) or darker by at least \( t \) , then the candidate point is considered to be a corner. For each detected corner, its strength is computed. Optionally, a non-maxima suppression step is applied on all detected corners to remove multiple or spurious responses.

Segment Test Detector

The FAST corner detector uses the pixels on a Bresenham circle of radius 3 (16 pixels) to classify whether a candidate point \( p \) is actually a corner, given the following variables.

\begin{eqnarray} I &=& \text{ input image } \\ p &=& \text{ candidate point position for a corner } \\ I_p &=& \text{ image intensity of the candidate point in image } I \\ x &=& \text{ pixel on the Bresenham circle around the candidate point } p \\ I_x &=& \text{ image intensity of the candidate point } \\ t &=& \text{ intensity difference threshold for a corner } \\ N &=& \text{ minimum number of contiguous pixel to detect a corner } \\ S &=& \text{ set of contiguous pixel on the Bresenham circle around the candidate point } \\ C_p &=& \text{ corner response at corner location } p \\ \end{eqnarray}

The two conditions for FAST corner detection can be expressed as:

C1: A set of \( N \) contiguous pixels \( S \), \( \forall x \) in \( S \), \( I_{x} > I_{p} + t \)
C2: A set of \( N \) contiguous pixels \( S \), \( \forall x \) in \( S \), \( I_{x} < I_{p} - t \)

So when either of these two conditions is met, the candidate \( p \) is classified as a corner.

In this version of the FAST algorithm, the minimum number of contiguous pixels \( N \) is 9 (FAST9).

The value of the intensity difference threshold strength_thresh. of type VX_TYPE_FLOAT32 must be within:

\[ {UINT8_{MIN}} < t < {UINT8_{MAX}} \]

These limits are established due to the input data type VX_DF_IMAGE_U8.

Corner Strength Computation

Once a corner has been detected, its strength (response, saliency, or score) shall be computed if nonmax_suppression is set to true, otherwise the value of strength is undefined. The corner response \( C_p \) function is defined as the largest threshold \( t \) for which the pixel \( p \) remains a corner.

Non-maximum suppression

If the nonmax_suppression flag is true, a non-maxima suppression step is applied on the detected corners. The corner with coordinates \((x,y)\) is kept if and only if

\begin{eqnarray*} C_p(x,y) \geq C_p(x-1,y-1) \; and \; C_p(x,y) \geq C_p(x,y-1) \; and \\ C_p(x,y) \geq C_p(x+1,y-1) \; and \; C_p(x,y) \geq C_p(x-1,y) \; and \\ C_p(x,y) > C_p(x+1,y) \; and \; C_p(x,y) >C_p(x-1,y+1) \; and \\ C_p(x,y) >C_p(x,y+1) \; and \; C_p(x,y) >C_p(x+1,y+1) \end{eqnarray*}

See also: http://www.edwardrosten.com/work/fast.html; http://en.wikipedia.org/wiki/Features_from_accelerated_segment_test

Functions
vx_node VX_API_CALL	vxFastCornersNode (vx_graph graph, vx_image input, vx_scalar strength_thresh, vx_bool nonmax_suppression, vx_array corners, vx_scalar num_corners)
	[Graph] Creates a FAST Corners Node. More...

vx_status VX_API_CALL	vxuFastCorners (vx_context context, vx_image input, vx_scalar strength_thresh, vx_bool nonmax_suppression, vx_array corners, vx_scalar num_corners)
	[Immediate] Computes corners on an image using FAST algorithm and produces the array of feature points. More...

Function Documentation

vx_node VX_API_CALL vxFastCornersNode	(	vx_graph	graph,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_bool	nonmax_suppression,
		vx_array	corners,
		vx_scalar	num_corners
	)

[Graph] Creates a FAST Corners Node.

Parameters

[in]	graph	The reference to the graph.
[in]	input	The input `VX_DF_IMAGE_U8` image.
[in]	strength_thresh	Threshold on difference between intensity of the central pixel and pixels on Bresenham's circle of radius 3 (`VX_TYPE_FLOAT32` scalar), with a value in the range of 0.0 \(\le\) strength_thresh < 256.0. Any fractional value will be truncated to an integer.
[in]	nonmax_suppression	If true, non-maximum suppression is applied to detected corners before being placed in the `vx_array` of `VX_TYPE_KEYPOINT` objects.
[out]	corners	Output corner `vx_array` of `VX_TYPE_KEYPOINT`. The order of the keypoints in this array is implementation dependent.
[out]	num_corners	[optional] The total number of detected corners in image. Use a VX_TYPE_SIZE scalar.

Returns: vx_node.

Return values

vx_node A node reference. Any possible errors preventing a successful creation should be checked using vxGetStatus

vx_status VX_API_CALL vxuFastCorners	(	vx_context	context,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_bool	nonmax_suppression,
		vx_array	corners,
		vx_scalar	num_corners
	)

[Immediate] Computes corners on an image using FAST algorithm and produces the array of feature points.