Nokia Cv Informational Slides

8/21/2019 Nokia Cv Informational Slides

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Learning More About NokiaCV

A Mobile Based Computer Vision

Algorithm Suite


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Current Scenario

Mobile cameras are widespread

Main uses for camera: capturing images/videos

Still significantbarriers to create new

applications

There is not enough supportfor

camera/imaging in S60 SDK

Only a handful of small companies making

camera apps. Most of these are experts

computer vision expertise, image/signal

processing experience


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Solution: Nokia Computer Vision

Library (NokiaCV) Developers do not have to start

imaging/camera applications from scratch

Shared platform will encourage further and

more complex work in imaging domain

Nokia Computer Vision library built on top

of Symbian

Fundamental operations for imaging and

camera processing


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Prior work

A few libraries available for mobile devices, includin

S60

Symbian mainly supports bitmap drawing, image/video

capture. No processing support

Difficult/slow to access individual pixelscommon

operation in processing

Other S60 imaging libraries are research-qualitycode, no support


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Goal

Internally to be used in imaging products, as aresearch test bed, etc.

Externally to provide developers in binary form

to facilitate third-party imaging Intels OpenCV is the desktop version of what

NCV will become for mobiles Full functionality

Wide range of imaging operations, however some notpossible on mobile (yet)

NokiaCVs main difference: supports operations thatare useful and fast right now.


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Use Cases


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Capture Enhancement

Image color conversions, imaging wrapper to modify images easilyand manipulate pixels directly and easily

Building blocks present for developers to make high-quality stitchingalgorithms for panoramas

Building blocks present for developers to implement complex

algorithms without requiring the building and debugging of aplatform


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Gaming/UI

Provides robust motion estimation as a software

component, ready for games and applications


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Post-capture editing

Image warping operation provided to createstandard warping or in other entertainment uses

Image compositing provided to add items to

captured images


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NokiaCV Library Overview

Library builds on OS, extending imaging

capabilities

Image object provided standardizing OS image

internals Standard image operations provided

Linear algebra used in many advanced imaging

applications, present in NCV Building block for future advanced libraries, both

externally and internally


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Functional Blocks


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CCamus

CEgoMovement

CEigenvalues

CFixed

CImageOp CArithmeticOp

CColorConversionOp

CComparisonOp

CConvolutionOp CCornerDetectionOp

CEdgeDetectionOp

CGaussianSmoothOp

CMedianFilterOp

CMorphologicalOp

CResizeOp

CRotationOp

CShearOp

CTemplateMatchOp

CThresholdOp

CWarpOp

CImageOperations

CImagePyramid

CImageStatistics

CMotionHistoryImage

CNokiaCVImage

CNokiaCVMath

CNokiaCVMatrix CNokiaCVVector

COpticalFlow CPixelAccess

CPixelColorModel

CSVD

TColorModel CHsvColorModel

CLabColorModel

CLmsColorModel

CRgbColorModel

CXyzColorModel CYuvColorModel
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API Overview

This library extends the image processing and math capabilities ofthe Symbian Series 60 platform, targeted for applications usingcomputer vision techniques on camera phones.

The library provides an image class, CNokiaCVImagefor handlingRGB, grayscale and black and white images. Provides functions toperform arithmetic operations, transformations, feature extraction,

color conversions. In addition, operations to compute imagestatistics such as histograms and pixel color means are provided.

The library has two algorithms (CCamusand CMotionHistoryImage)to determine motion estimates and history.

Matrix and vector classes CNokiaCVMatrixand CNokiaCVVectorallow creation of matrices and vectors of arbitrary dimensionality.

Math operations and some linear algebra techniques that work withthese classes are available in the library.
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Library Features


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CNokiaCVImage Class

CNokiaCVImageis a wrapper for CFbsBitmap that isprovided by the platform. This class providesDisplayMode independent access to the pixel data.CFbsBitmap* iInternalBitmap;

Usage examples:// load from file

CNokiaCVImage* incvBitmap = CNokiaCVImage::NewL();

TRAPD(err1, incvBitmap->CreateL( *aImageFullName )); ...

// draw bitmap

CWindowGc& gc = SystemGc();

gc.BitBlt( TPoint( 0,0 ), incvBitmap-> Bitmap());
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Functions

static IMPORT_C CNokiaCVImage*CNokiaCVImage::NewLC ( ) ; Implements two-phaseconstruction functions (NewLC(), ConstructL()) tocreate a new instance of the object.

Returns: CNokiaCVImage*

IMPORT_C void CNokiaCVImage::CreateL (const TDesC& aFileName ) ; Create image from a file.

static IMPORT_C void CNokiaCVImage::Copy(CNokiaCVImage* aSource, CNokiaCVImage* aTarget,TInt aBlendingRatio = 100); Copy a source imageto the target image.
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CPixelAccess Class

CPixelAccessclass provides access toCNokiaCVImageon a pixel-level. Derived fromTBitmapUtil.

Example:

CPixelAccess* out = CPixelAccess::NewL(aTarget);CPixelAccess* in = CPixelAccess::NewL(iImage, out);...in->SetPos( TPoint( rotX, rotY ) );out->SetPos(TPoint( x, y ) );out->SetRGB( in->GetRGB()); // set pixel value from into out...delete out;delete in;
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Functions

static IMPORT_C CPixelAccess* CPixelAccess::NewLC(CNokiaCVImage* aImage ) ; Constructor. Sets thecurrent pixel position to (0,0) position.

IMPORT_C TUint32 CPixelAccess::GetRGB ( ) ; Returnpixel from the current position as a RGB.

IMPORT_C void CPixelAccess::SetRGB(TUint32 aPixel ) ; Set pixel to the current

position.Parameters:

aPixelRGB value as TUint32 in format used byTRgb: 0x00BBGGRR
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CPixelColorModel Class

IMPORT_C TUint8 CPixelColorModel::Red ( ) ; Getthe red component;

Returns: TUint8 Red-component

IMPORT_C CYuvColorModelCPixelColorModel::ToYUV( ) ; Convert to YUV.

Returns: CYuvColorModel.

IMPORT_C CHsvColorModelCPixelColorModel::ToHSV( ) ;

Convert to HSV

return CHsvColorModel
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TColorModel Class

class CRgbColorModel : public TColorModel{

public:TInt iR;TInt iG;TInt iB;};

class CYuvColorModel : public TColorModel{

public:

TInt iY;TInt iU;TInt iV;};


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CNokiaCVMath Class

This class gathers some utility functions in one place.

static IMPORT_C TInt SinLUT_Rad(TReal&aTrg, const TReal &aSrc)Computes Sinusing lookup table.

static IMPORT_C TInt TanLUT_Rad(TReal&aTrg, const TReal &aSrc) Computes Tanusing lookup table.
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CNokiaCVMatrix Class

Fixed point matrix representation. Usage:CNokiaCVMatrix* m = CNokiaCVMatrix->NewLC(5,5);

(*m)(3,3) = 2; (*m)(2,3) = 4.23;

CNokiaCVMatrix* n = CNokiaCVMatrix->Ones(5,5);CleanupStack::PushL(n);

CNokiaCVMatrix*res = (*m)*(*n)*5;

CleanupStack::PushL(res);

CFixeddet = res->Det();

...CleanupStack::Pop(m); CleanupStack::Pop(n);CleanupStack::Pop(res);

delete m; delete n; delete res;
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Functions

static IMPORT_C CNokiaCVMatrix*NewL(const TIntaRows, const TInt aCols)Creates a new matrixaccording to size given with initial value zero.

IMPORT_C CNokiaCVMatrix* Inverse()const Calculates the inverse matrix of this

matrix.

IMPORT_C CFixed** Eigenvalues() Calculates theeigenvalues of this matrix.

IMPORT_C CFixed* Singularvalues() Calculates thesingular values of this matrix using ncvSVD.
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CSVD Class

Singular value decomposition of a given real matrix.

Householder bidiagonalization and a variant of the QR algorithm are

used.

The SVD algorithm is derived from JAMA/TNT, the Java Matrix

Package. Usage:

CNokiaCVMatrix*a = CNokiaCVMatrix::NewL(rows,cols);

CSVD*svd;

TRAPD(err, svd = CSVD::NewL(*a))

... //Handle possible errorsCNokiaCVMatrix*v = svd->V();

...

delete a; delete svd; delete v;
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CNokiaCVVector Class

Fixed point representation of a vector.

classCNokiaCVVector : publicCNokiaCVMatrix

{

IMPORT_C TInt Length()Getter of the vector size/length.

IMPORT_C CNokiaCVVector* Normalize() Creates thenormalization of this vector.

IMPORT_C CNokiaCVVector* CrossProduct(CNokiaCVVector&aVector) Calculates the cross product of this and the givenvector.

IMPORT_C CFixedDotProduct(CNokiaCVVector&aVector) Calculatesthe dot product of to same size vectors.
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CMotionHistoryImage Class

This class computes a motion history image (MHI) for a series ofinput frames. The MHI is a grayscale bitmap in which recentlymoved pixels are represent with bright values and "older" withdarker values. Frame-by-frame the values from previous frames aredecayed linearly.


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Functions

static IMPORT_C CMotionHistoryImage*NewL(CNokiaCVImage&aImage, const TIntaHistorySize)Construct CMotionHistoryImagefrom thefirst image of motion history.

Parameters:aImageSize Size of the images.aHistorySize Maximum number of images in thehistory.

IMPORT_C voidAddImage(CNokiaCVImage&aImage) Add animage to the motion history.

IMPORT_C void GetImage(CNokiaCVImage&aImage) Get aCNokiaCVImagecontaining the motion history image.
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COpticalFlow Class

The optical flow class: motion estimations for each pixel.This class also implements methods for calculatinghigher level information from the optical flow.

Friends class CCamus: Camus algorithm forestimation of optical flow from a series of bitmaps.

Member CEgoMovement Class: class for pixel motion

estimation values.CFixediXMovement along the x-axis.

CFixediYMovement along the y-axis .
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Functions

static IMPORT_C COpticalFlow*NewL(const TSize&aImageSize)Factory method for creating aninstance.Parameters: aImageSize Size of the optical flow map

IMPORT_C CEgoMovementMean() const Calculate themean value of the optical flow. Represents tiltingand panning of the camera.

IMPORT_C CFixedRotation()Calculate the meanrotation of the optical flow in the image plane.
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Functions

void SetCamusOpts(const TInt aCamusOpts)Setruntime parameters of the Camus motion estimationalgorithm.

IMPORT_C CEgoMovement(const CFixedaX, constCFixedaY)Constructor.

IMPORT_C CFixedNorm() Calculates the euclidian

norm of the movement.
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CImagePyramid Class

Creates a Laplacian or Gaussian image pyramid from a givenbitmap.

IMPORT_C CNokiaCVImage* LevelImage(TIntaLevel)Getter for an image of certain level.

Returns: CNokiaCVImage* Pointer to the level image

static IMPORT_C CImagePyramid* NewLC(CNokiaCVImage*aImage, TInt aLevels,TImagePyramidType

aType=EGaussianPyramid)Constructor.

Parameters:

aImage CNokiaCVImageto construct the pyramid fromaLevels How many levels in the pyramid. If the numberis too large it will be truncated. aType Which type of

pyramid to construct. Default = Gaussian.
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CImageStatistics Class

Calculating various statistics from CNokiaCVImages. CImageStatisticsprovides the following statistical functions for CNokiaCVImages:

Histogram

Mean

Standard deviation

Image moments:

m00 m01

m10

m11

m20

M02

Usage:

TReal mean; CImageStatistics::Mean(*iSourceBitmap, mean,(TChannel)aChannel);
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Functions

static IMPORT_C void Histogram(CNokiaCVImage&aImage, THistogram &aArray, TChannelaChannel=EGrayChannel)Calculate the histogramfrom a CNokiaCVImage.

static IMPORT_C voidMean(CNokiaCVImage&aImage,TReal &aMean, TChannelaChannel=EAllChannels) Calculate the mean ofCNokiaCVImage.static IMPORT_C void StDev(CNokiaCVImage&aImage,TReal &aStDev, TReal &aMean, TChannel

aChannel) Calculate the standard deviation of aCNokiaCVImage.
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CImageOperations Class

Provides an simplified access to image operations. Each operation

is a static method that creates and returns the result bitmap.

UsageCNokiaCVImage* iTarget =CImageOperations::Rotate(iSource, 45);

...

delete iTarget;


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Functions

static IMPORT_C CNokiaCVImage* Resize(CNokiaCVImage*aSource, TSize aSize, TBool aBilinear=EFalse)Resizesthe source image. See CResizeOpfor more information.

static IMPORT_C CNokiaCVImage* Convolution(CNokiaCVImage*aSource, CNokiaCVMatrix&aKernel, TIntaNormFactor) Performs convolution of CNokiaCVImageand akernel (CNokiaCVMatrix).

static IMPORT_C CNokiaCVImage* Gaussian(CNokiaCVImage*aSource, TUint aSize) Gaussian smoothing filter.

static IMPORT_C CNokiaCVImage* EdgeDetectLaplacian

(CNokiaCVImage*aSource) Laplacian edge detectionfilter. See CEdgeDetectionOpfor more info.
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CCamus Class

Implements the Camus algorithm for estimation of optical flow from a seriesof bitmaps. This class creates an COpticalFlowobject that contains anestimation of the motion vector (x and y motion in pixels) for each pixel ofthe input frame.

Can use the methods of COpticalFlowto extract higher level informationsuch as estimated camera rotation/movement.

The algorithm is highly parameterizable. Features of the algorithm and some hints: Maximum estimated motion is 1 or 2 pixels/frame, so it is typically reasonable to

use small bitmaps (e.g. 16x12 pixels).

History of several frames is used to achieve sub pixel accuracy

Based on template matching

Uses grayscale images

Large motions are hard so having a good frame rate is essential since the per-frame motion is inversely proportional to the frame rate

Small bitmaps are preferred (especially when estimation of quick movements isrequired) as its faster to compute; higher frame rate.
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Camus Algorithm

Basic idea:

Simple technique to perform optical flowcomputations using correlation or patch-

making methods. The idea here is to matchfeatures between images and computing theSD (sum-difference) of patches.

Reference: T. Camus, Real-Time OpticalFlow, PhD Thesis, Brown UniversityTechnical Report CS-94-36, 1994.


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Functions

static IMPORT_C CCamus* CCamus::NewL

(CNokiaCVImage& aImage,

const TInt aHistorySize=KDefaultCamusHistorySize )

IMPORT_C void CCamus::GetOpticalFlow (COpticalFl& aOpticalFlow, CNokiaCVImage& aImage, constTInt aCamusOpts= KDefaultCamusOpts )
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How to Use CCamus

COpticalFlow* iOpticalFlow =COpticalFlow::NewL(iFirstFrame->Size());

CNokiaCVImage* iCamus = CCamus::NewL(*iFirstFrame,5);

iCamus->GetOpticalFlow(*iOpticalFlow, *iSecondFrame,CAMUS_SETCAMUSOPTS(CCamus::EMedium,CCamus::EMedium, 3));

CEgoMovementmean = iOpticalFlow->Mean();
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CEgoMovement Class

Simple vector-like wrapper class for pixel

motion estimation values.


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Functions IMPORT_C CEgoMovement::CEgoMovement (const

CFixedaX, const CFixedaY)Constructor.Parameters: aXMovement along the x-axis. aYMovement along the y-axis.

IMPORT_C CFixedCEgoMovement::Norm ( )Calculatesthe Euclidian norm of the movement.Returns:Norm (the length of the movement in cartesian

coordinate system).

IMPORT_C CFixedCEgoMovement::DotProduct (constCEgoMovement& aMovement )Calculates a dotproduct.Parameters: aMovementVector movement.

Returns:

Dot product value.
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CEigenValues Class

Eigenvalue decomposition of a real matrix.Usage:CNokiaCVMatrix* matrix = ...; CEigenvalues*eigs;

TRAPD(err, eigs = CEigenvalues->NewL(matrix));if(err != KErrNone) {

//eigs not found do something

}

else {

TReal * real = eigs->RealEigenvalues();delete eigs;

} ...
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Functions

IMPORT_C TReal*CEigenvalues::RealEigenvalues ( )Getter for the real part of theeigenvalues (iD).Returns: the real part of the eigenvalues in an array

IMPORT_C TReal*CEigenvalues::ImaginaryEigenvalues ( )Getter for the imaginary part of theeigenvalues (iE).Returns: the imaginary part of the eigenvalues in anarray


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CFixed Class

Fixed point class.

The class implements basic arithmetic for

fixed point numbers.

CFixedcan be used instead of TReal

when performance more critical than

accuracy.
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CImageOp Class

Image operations interface. This class represents an interface that all image operation classes

must implement. Most of the operations implementing this interfaceare also included in CImageOperations.

There are various image operations that implement this interface,e.g. for rotating, scaling and filtering bitmap.

Usage example (CRotationOp):

iSource = ....iTargetMode = EGray256;iTarget1 = CNokiaCVImage::NewL();

iTarget1->CreateL(iCurrSource->Size(),iTargetMode);CRotationOpop(iCurrSource, 90);op.DoOperation(iTarget1); ...
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Functions

virtual IMPORT_C void CImageOp::DoOperation(CNokiaCVImage* aTarget )[pure virtual]

All image operations must implement this method. This method doesthe actual operation.

Typically you need to allocate and create the target bitmap yourselfbefore doing the operation

Parameters: aTargettarget bitmap

Note: the function can leave

Implemented in CArithmeticOp, CColorConversionOp,

CComparisonOp, CConvolutionOp, CCornerDetectionOp,CEdgeDetectionOp, CGaussianSmoothOp, CMedianFilterOp,CMorphologicalOp, CResizeOp, CRotationOp, CShearOp,CTemplateMatchOp, CThresholdOp, and CWarpOp.
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CArithmeticOp

CArithmeticOpprovides basic arithmetic operations forCNokiaCVImages.

Target and source bitmaps must be of same size.

Usage:

IMPORT_C void CArithmeticOp::DoOperation(CNokiaCVImage* aTarget )

Does the actual operation.

Parameters:

aTargetCNokiaCVImageto store the result in. Must be allocatedand created beforehand.

Implements CImageOp.
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Image Arithmetic Examples


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CColorConversionOp Class

Provides CNokiaCVImage with color

conversions.


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Functions

IMPORT_C CColorConversionOp::CColorConversionOp(CNokiaCVImage* aImage, TDisplayMode aTargetMode)

Constructor. Converts given image to given display mode.

Parameters: aImageImage to convert aTargetModeTarget display mode Valid

TDisplayModes for aTargetMode are: EGray2

EGray4 EGray16

EGray256

EColor4K

EColor64K

EColor16M

IMPORT_C void CColorConversionOp::DoOperation(CNokiaCVImage* aTarget )

Parameters: aTargetCNokiaCVImageto store the result in.
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CComparisonOp Class

Provides CNokiaCVImagewith pixel-wise imagecomparison operations: "greater than", "lessthan" and "equal".

Matching pixels are set white. Non-matching andpixels outside the comparison region are setblack.

Valid values are: EGreater

ELess

EEqual
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Functions

IMPORT_C CComparisonOp::CComparisonOp (CNokiaCVImage* aImage1,CNokiaCVImage* aImage2,TComparisonTypeaComparison)Constructor.Parameters: aImage1images to compare aImage2another images to compare.

aComparisonComparison operation: .EGreater, ELess or EEqual

IMPORT_C CComparisonOp::CComparisonOp (CNokiaCVImage* aImage1,CNokiaCVImage* aImage2, TComparisonTypeaComparison,TRect aSubregion)Constructor.Parameters: aImage1images to compare aImage2another images to compare. These two images must

be of same bit depth and same size

aComparisonComparison operation: .EGreater, ELess or EEqual

aSubregionsubregion of images 1 and 2 that are compared

IMPORT_C void CComparisonOp::DoOperation (CNokiaCVImage* aTarget )

Parameters: aTargetCNokiaCVImageto store the result in. The target bitmap must be black and white.
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CConvolutionOp Class

Convolution operation.

Performs convolution of CNokiaCVImage

and a kernel (CNokiaCVMatrix).

O57 = I56K11+ I58K12+ I59K13+ I67K21+ I68K22+ I69K23
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Functions

IMPORT_C CConvolutionOp::CConvolutionOp(CNokiaCVImage* aImage, CNokiaCVMatrix& aKernel)Constructor.

Parameters:

aImageCNokiaCVImageto use as sourceaKernelCNokiaCVMatrixKernel to use for convolution. Only 3x3and 5x5 matrices are supported.

IMPORT_C void CConvolutionOp::DoOperation(CNokiaCVImage* aTarget )

Parameters: aTargetCNokiaCVImageto store the result in.
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CCornerDetectionOp

Corner detection for CNokiaCVImage.

Moravec corner detector is implemented.

Defines interest points as points where there

is a large intensity variation in every direction

i.e. corners.


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Functions

IMPORT_C CCornerDetectionOp::CCornerDetectionOp(CNokiaCVImage* aImage,TCornerDetectionMethodaMethod= EMoravec,TInt aNeighborhoodSize= 20, TInt aConstant= 25 )Constructor.

Parameters:

aImageCNokiaCVImageto detect from aMethodWhich corner detection method to use

aNeighborhoodSizeSize of the neighborhood to use for adaptivethresholding

aConstanta constant value to subtract from the mean threshold

IMPORT_C void CCornerDetectionOp::DoOperation

(CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result
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CEdgeDetectionOp

Edge detection filters using convolution.

Possible values are: ESobel

EPrewitt

ELaplacian ECanny

Canny edge detection with different convolution sizes


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Functions

IMPORT_CCEdgeDetectionOp::CEdgeDetectionOp(CNokiaCVImage* aImage,TEdgeDetectionMethodaMethod)Constructor.

Parameters: aImageCNokiaCVImageto detect from aMethodWhich edgedetection method to use

IMPORT_C voidCEdgeDetectionOp::DoOperation

(CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result
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CGaussianSmoothOp

Gaussian smoothing operator.

The Gaussian smoothing operator is a 2-D

convolution operator used to `blur' images

and remove detail and noise.

The shape of the kernel represents the

shape of a Gaussian (`bell-shaped') point-

spread function.

5 X 5 Gaussian Kernel


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Functions

IMPORT_CCGaussianSmoothOp::CGaussianSmoothOp(CNokiaCVImage* aImage,TInt aKernelSize)Constructor.

Parameters: aImageCNokiaCVImagea source image aKernelSizeThenumber of rows and columns in Gaussian kernel: Possiblevalues are. 3 and 5.

IMPORT_C void

CGaussianSmoothOp::DoOperation(CNokiaCVImage* aTarget )

Parameters: aTargetCNokiaCVImageto store the result
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CMedianFilterOp

Median filter operation. The median filter is normally used to reduce noise in an image.

Does a reasonable job of preserving useful detail in the image.

Replaces every pixel with the medianof its neighboring pixels.

Median Filter 3X3


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Functions

IMPORT_C CMedianFilterOp::CMedianFilterOp(CNokiaCVImage* aImage,TInt aKernelRows)Constructor.

Parameters:

aImageCNokiaCVImageto use as source aKernelRowsHowbig a kernel to use. Possible values are: 3 for 3x3

5 for 5x5

7 for 7x7

IMPORT_C void CMedianFilterOp::DoOperation

(CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result in.


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CMorphologicalOp Class

Dilation/Erosion filter. Here, the state of any given pixel in the output image is

determined by applying a rule to the corresponding pixeland its neighbors in the input image. The rule used toprocess the pixels defines the operation as a dilation or

an erosion. Dilation:The value of the output pixel is the maximum

value of all the pixels in the input pixel's neighborhood.In a binary image, if any of the pixels is set to the value1, the output pixel is set to 1.

Erosion:The value of the output pixel is the min imumvalue of all the pixels in the input pixel's neighborhood.In a binary image, if any of the pixels is set to 0, theoutput pixel is set to 0.


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Functions

IMPORT_C CMorphologicalOp::CMorphologicalOp(CNokiaCVImage* aImage, CNokiaCVMatrix& aStruct,TMorphologicalOperationaOperation)Constructor.Parameters: aImageCNokiaCVImageto use as source

aStructCNokiaCVMatrixa structuring element to use for morphing

aOperationWhich operation to do

IMPORT_C void CMorphologicalOp::DoOperation(CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result in.
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CResizeOp Class

Resizes the CNokiaCVImage.

IMPORT_C CResizeOp(CNokiaCVImage*aImage, TBool

aBilinear=EFalse)Constructor.

IMPORT_C void DoOperation(CNokiaCVImage*aTarget)

Do the actual resize. Take the new size

from target image and store the result in it.
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CRotationOp Class

Rotates a CNokiaCVImage.

Implements an arbitrary angle rotation.

IMPORT_C CRotationOp

(CNokiaCVImage*aImage, TIntaAngle) Constructor.


Do the actual operation.
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CShearOp Class

Shear operation for CNokiaCVImage.

Shears bitmap Horizontally or Vertically (createsa parallelogram).

IMPORT_C CShearOp(CNokiaCVImage*aImage, TInt aAngle, TDirectionaDirection=EHorizontal)Constructor.


Do the actual operation.
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CTemplateMatch Class

Template matching operation for two CNokiaCVImages. Used for finding small parts of an image that match a

template image.

Algorithm:

This method is implemented by first creating a subimage (thetemplate).

The center of the subimage is simply moved over each (x,y)point in the a candidate image.

The sum of products between the coefficients in the candidateimage and the corresponding neighborhood pixels in the areaspanned by the template is calculated to determine best match.

Also applicable for color images.


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Functions

IMPORT_C CTemplateMatchOp::CTemplateMatchOp(CNokiaCVImage* aImage, CNokiaCVImage* aTemplate)Constructor for template matching operation.

Parameters: aImageCNokiaCVImageto match against aPattern

CNokiaCVImagecontaining the template to match

IMPORT_C void CTemplateMatchOp::DoOperation(CNokiaCVImage* aTarget= NULL )Parameters: aTargetCNokiaCVImageto store the resulting correlation values

Implements CImageOp.

IMPORT_C void CTemplateMatchOp::DoOperation (TPoint& aPoint, CNokiaCVMatrix* aCorrMatrix= NULL )Parameters: aPointresulting matching poin

aCorrMatrixcorrelation matrix
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CThresholdOp

Provides CNokiaCVImagewith a threshold operation. Thresholding is the most common method of segmenting images into

particle regions and background regions.

Creates an black and white bitmap from CNokiaCVImageby thresholding.

Implements two thresholding methods: simple with static threshold value

Local adaptive: Selects an individual threshold for each pixel based on the rangeof intensity values in its local neighborhood. This allows for thresholding of animage whose global intensity histogram doesn't contain distinctive peaks.
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Functions

IMPORT_C CThresholdOp::CThresholdOp (CNokiaCVImage* aImage,TUint8 aThresholdValue)Constructor for thresholding with given value.

Parameters: aImageCNokiaCVImageto apply the thresholding to.

aThresholdValuean integer value (0-255) to use as a threshold.

IMPORT_C CThresholdOp::CThresholdOp (CNokiaCVImage* aImage,TInt aSize, TInt aConstant, TThresholdType= EMean )Constructor for adaptive thresholding.

Parameters: aImageCNokiaCVImageto apply the thresholding to.

aSizeaSize x aSize neighborhood to use for adaptation

aConstantConstant value that is subtracted from the mean.

IMPORT_C void CThresholdOp::DoOperation (CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result in.
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CWarpOp Class

Provides CNokiaCVImagewith a warp operation Theresult of the operation is like dragging an elastic imagefrom one point to a given direction.

IMPORT_C CWarpOp::CWarpOp (CNokiaCVImage* aImage, TPoint aSource,

TPoint aDestination)Constructor.

Parameters: aImageSource image. aSourceSource point to start the warp

from. aDestinationDestination point to warp towards.

IMPORT_C void CWarpOp::DoOperation(CNokiaCVImage* aTarget )Parameters: aTargetCNokiaCVImageto store the result in.


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Demos


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Outline

Cube

Motion Estimation

Image Processing

Game


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Cube Using a cube to represent camera movement

Obtaining optical flow using Camus algorithm

Mean movement of optical flowCubes movement

along x and y

Mean rotation of optical flowCubes rotation

Depth info: movement along z axis Cubes size

NokiaCV classes used

CCamus

CEgoMovement COpticalFlow

CNokiaCVImage

CPixelAccess


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Motion Estimation

Calculate and display motion history image

Calculate optical flow, indicate horizontal and

vertical motion

NokiaCV classes used CMotionHistoryImage

CNokiaCVImage

CCamus

COpticalFlow


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Image Processing

Loads two images

Perform image processing based on user

selection

NokiaCV classes used

All image processing classes

Documents

Nokia Cv Informational Slides