Computes the Harris corner detection response on a 3d image. More...

IPSDKIPLFEATUREDETECTION_API image::ImagePtr	ipsdk::imaproc::fd::harrisCorner3dImg (const ipsdk::image::ImageConstPtr &pInImg3d)
	wrapper function for Computes the Harris corner detection response on a 3d image More...

IPSDKIPLFEATUREDETECTION_API image::ImagePtr	ipsdk::imaproc::fd::harrisCorner3dImg (const ipsdk::image::ImageConstPtr &pInImg3d, const ipsdk::ipReal32 inGradStdDev)
	wrapper function for Computes the Harris corner detection response on a 3d image More...

IPSDKIPLFEATUREDETECTION_API void	ipsdk::imaproc::fd::harrisCorner3dImg (const ipsdk::image::ImageConstPtr &pInImg3d, const ipsdk::ipReal32 inGradStdDev, const attr::GaussianCoverageConstPtr &pInOptGradientGaussianCoverage, const ipsdk::imaproc::attr::CornerDetectionParamsConstPtr &pInCornerDetectionParams, const ipsdk::image::ImagePtr &pOutImg)
	wrapper function for Computes the Harris corner detection response on a 3d image More...

Detailed Description

Computes the Harris corner detection response on a 3d image.

This algorithm is the 3d extension of the Harris corner detection 2d image algorithm [1] proposed by I. Laptev [2] and computes the cornerness for each pixel of the input 3d image. This algorithm also support a extension of Shi-Tomasi [3] [4] corner detector algorithm to 3d case.

As an extension of 2d case, $M$ is defined as follows :

$M = \sum_{x, y, z \in \aleph}{\omega(x, y, z) \begin{bmatrix} I_x^2 & IxIy & IxIz\\ IxIy & Iy^2 & IyIz\\ IxIz & IyIz & Iz^2 \end{bmatrix}}$

With $Ix$ , $Iy$ and $Iz$ are the spatial derivatives of the input image along the directions $x$ , $y$ , and $z$ respectively and $\omega(x, y, z)$ is a Gaussian weight in the neighbourhood $\aleph$ .

If selected method is set to ipsdk::imaproc::attr::eCornerDetectionMethod::eCDM_Harris (which is the default value) the cornerness is calculated at the position by :
$C(u, v, w) = det(M) - k \left( trace(M) \right)^3$
Where is the sensitivity corresponding to the parameter , is the determinant of and is the trace of .
In order to fit into the output image range, the algorithm returns the cube root of :
$OutImg(u, v, w) = \sqrt[\leftroot{3}3]{C(u, v, w)}$
If selected method is set to ipsdk::imaproc::attr::eCornerDetectionMethod::eCDM_ShiTomasi the cornerness can be computed at the position by :
$C(u, v, w) = OutImg(u, v, w) = \min(\lambda_1, \lambda_2, \lambda_3)$
where $\lambda_1$ , $\lambda_2$ and $\lambda_3$ correspond to eigen values of matrix (in this case sensitivity contained by parameter is ignored).

See Harris corner detection 2d image for more details on the algorithm and for an illustration of the Harris corner detection algorithm in the 2d case.

[1] C. Harris and M. Stephens (1988). "A combined corner and edge detector". Proceedings of the 4th Alvey Vision Conference. pp. 147 - 151.
[2] I. Laptev. "On space-time interest points". IJCV , 64(2-3):107 - 123, 2005.
[3] J. Shi and C. Tomasi (June 1994). "Good Features to Track". 9th IEEE Conference on Computer Vision and Pattern Recognition. Springer
[4] C. Tomasi and T. Kanade (2004). "Detection and Tracking of Point Features". Pattern Recognition. 37: 165 - 168

Attributes description

Attribute description for algorithm :

Name	ToolTip	Default Initializer
ipsdk::imaproc::attr::InImg3d	[Input] 3d image for operation	X
ipsdk::imaproc::attr::InOptGradStdDev	[Input Optional] standard deviation used for gradient computation	X
ipsdk::imaproc::attr::InOptGradientGaussianCoverage	[Input Optional] Parameter allowing to specify a gaussian distribution coverage for processing	X
ipsdk::imaproc::attr::InOptCornerDetectionParams3d	[Input Optional] parameters used during corner detection process	X
ipsdk::imaproc::attr::OutWk1Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk1Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutWk2Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk2Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutWk3Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk3Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutWk4Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk4Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutWk5Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk5Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutWk6Img	[Output] Temporary working image for algorithm	promoteUnary (_pOutWk6Img, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)
ipsdk::imaproc::attr::OutImg	[Output] image for processing operation	promoteUnary (_pOutImg, _pInImg3d, ipsdk::imaproc::ePromoteUnaryType::ePUT_UpperSigned)

Global Rule description

Global rule description for algorithm :
matchSize (_pInImg3d,_pOutImg) &&
matchSizeAndType (_pOutImg,_pOutWk1Img) &&
matchSizeAndType (_pOutWk1Img,_pOutWk2Img,_pOutWk3Img,_pOutWk4Img,_pOutWk5Img,_pOutWk6Img)

Example of Python code :

Example imports

import PyIPSDK

import PyIPSDK.IPSDKIPLFeatureDetection as fd

Code Example

# Harris corner detection

outImg = fd.harrisCorner3dImg(inImg)

Example of C++ code :

Example informations

Associated library

IPSDKIPLFeatureDetection

Header file

#include <IPSDKIPL/IPSDKIPLFeatureDetection/Processor/HarrisCorner3dImg/HarrisCorner3dImg.h>

Code Example

    // Sample with a generated output image
    // ------------------------------------
    ImagePtr pAutoOutImg = harrisCorner3dImg(pInImg);
    // Sample with a provided output image
    // ------------------------------------
    // create output image
    const ipUInt64 sizeX = pInImg->getSizeX();
    const ipUInt64 sizeY = pInImg->getSizeY();
    const ipUInt64 sizeZ = pInImg->getSizeZ();
    ImageGeometryPtr pOutputImageGeometry = geometry3d(outType, sizeX, sizeY, sizeZ);
    boost::shared_ptr<MemoryImage> pOutImg(boost::make_shared<MemoryImage>());
    pOutImg->init(*pOutputImageGeometry);
    // compute harris image
    harrisCorner3dImg(pInImg, stdDev, createGaussianCoverage(gaussRatio, 2), createHarrisParams(sensitivity), pOutImg);

See also: HarrisCorner3dImgLvl1; HarrisCorner3dImgLvl2; HarrisCorner3dImgLvl3

Function Documentation

◆ harrisCorner3dImg() [1/3]

IPSDKIPLFEATUREDETECTION_API image::ImagePtr ipsdk::imaproc::fd::harrisCorner3dImg ( const ipsdk::image::ImageConstPtr & pInImg3d )

wrapper function for Computes the Harris corner detection response on a 3d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException on failure

◆ harrisCorner3dImg() [2/3]

IPSDKIPLFEATUREDETECTION_API image::ImagePtr ipsdk::imaproc::fd::harrisCorner3dImg	(	const ipsdk::image::ImageConstPtr &	pInImg3d,
		const ipsdk::ipReal32	inGradStdDev
	)

wrapper function for Computes the Harris corner detection response on a 3d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException on failure

◆ harrisCorner3dImg() [3/3]

IPSDKIPLFEATUREDETECTION_API void ipsdk::imaproc::fd::harrisCorner3dImg	(	const ipsdk::image::ImageConstPtr &	pInImg3d,
		const ipsdk::ipReal32	inGradStdDev,
		const attr::GaussianCoverageConstPtr &	pInOptGradientGaussianCoverage,
		const ipsdk::imaproc::attr::CornerDetectionParamsConstPtr &	pInCornerDetectionParams,
		const ipsdk::image::ImagePtr &	pOutImg
	)

wrapper function for Computes the Harris corner detection response on a 3d image

Exceptions

ipsdk::processor::IPSDKBaseProcessingException on failure