Kernel: Harris Corners

Functions
VX_API_ENTRY vx_node VX_API_CALL	vxHarrisCornersNode (vx_graph graph, vx_image input, vx_scalar strength_thresh, vx_scalar min_distance, vx_scalar sensitivity, vx_int32 gradient_size, vx_int32 block_size, vx_array corners, vx_scalar num_corners)
	[Graph] Creates a Harris Corners Node.
VX_API_ENTRY vx_status VX_API_CALL	vxuHarrisCorners (vx_context context, vx_image input, vx_scalar strength_thresh, vx_scalar min_distance, vx_scalar sensitivity, vx_int32 gradient_size, vx_int32 block_size, vx_array corners, vx_scalar num_corners)
	[Immediate] Computes the Harris Corners over an image and produces the array of scored points.

Detailed Description

Function Documentation

vxHarrisCornersNode()

VX_API_ENTRY vx_node VX_API_CALL vxHarrisCornersNode	(	vx_graph	graph,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_scalar	min_distance,
		vx_scalar	sensitivity,
		vx_int32	gradient_size,
		vx_int32	block_size,
		vx_array	corners,
		vx_scalar	num_corners )

#include <vx_nodes.h>

[Graph] Creates a Harris Corners Node.

Parameters

[in]	graph	The reference to the graph.
[in]	input	The input VX_DF_IMAGE_U8 image.
[in]	strength_thresh	The VX_TYPE_FLOAT32 minimum threshold with which to eliminate Harris Corner scores (computed using the normalized Sobel kernel).
[in]	min_distance	The VX_TYPE_FLOAT32 radial Euclidean distance for non-maximum suppression.
[in]	sensitivity	The VX_TYPE_FLOAT32 scalar sensitivity threshold \( k \) from the Harris-Stephens equation.
[in]	gradient_size	The gradient window size to use on the input. The implementation must support at least 3, 5, and 7.
[in]	block_size	The block window size used to compute the Harris Corner score. The implementation must support at least 3, 5, and 7.
[out]	corners	The array of VX_TYPE_KEYPOINT objects. 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

Examples

optical_flow.cpp.

vxuHarrisCorners()

VX_API_ENTRY vx_status VX_API_CALL vxuHarrisCorners	(	vx_context	context,
		vx_image	input,
		vx_scalar	strength_thresh,
		vx_scalar	min_distance,
		vx_scalar	sensitivity,
		vx_int32	gradient_size,
		vx_int32	block_size,
		vx_array	corners,
		vx_scalar	num_corners )

#include <vxu.h>

[Immediate] Computes the Harris Corners over an image and produces the array of scored points.

Parameters

[in]	context	The reference to the overall context.
[in]	input	The input VX_DF_IMAGE_U8 image.
[in]	strength_thresh	The VX_TYPE_FLOAT32 minimum threshold which to eliminate Harris Corner scores (computed using the normalized Sobel kernel).
[in]	min_distance	The VX_TYPE_FLOAT32 radial Euclidean distance for non-maximum suppression.
[in]	sensitivity	The VX_TYPE_FLOAT32 scalar sensitivity threshold \( k \) from the Harris-Stephens equation.
[in]	gradient_size	The gradient window size to use on the input. The implementation must support at least 3, 5, and 7.
[in]	block_size	The block window size used to compute the harris corner score. The implementation must support at least 3, 5, and 7.
[out]	corners	The array of VX_TYPE_KEYPOINT structs. 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

A vx_status_e enumeration.

Return values

VX_SUCCESS	Success
*	An error occurred. See vx_status_e.