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Computer Vision and Apps

Antonio Radesca

Developer-Architect

MCPD

antrad@libero.it

antonio@nextgenerationteam.com

Fiore Rosalba

www.fiorerosalba.biz

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Computer Vision

• Transformation of data from a still or video camera into either a decision or a new representation.

• Data - > “the camera is mounted in a car” or “laser range fi nder indicates an object is 1 meter away”.

• Decision -> “there is a person in this scene” or “there are 14 tumor cells on this slide”

• New representation -> turning a color image into a grayscale image

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Machine prospective

• A 2d Image of a 3d object.• No definite way to reconstruct the 3d

image.

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Machine prospective

• Images are corrupted by noise and distortions.

• (weather, lighting, reflections, movements)

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OpenCV

• OpenCV (Open Source Computer Vision)

• library of programming functions for real time computer vision. (computer efficiency)

• Written in optimized C and C++• Runs in windows, Linux and MAC OS.• Can develop in C, C++, python, ruby,

matlab,Java,.NET

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OpenCV

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OpenCV

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Applications

• Human-Computer Interaction (HCI)• Object Identification, Segmentation and

Recognition• Face Recognition• Motion Tracking, Ego Motion, Motion

Understanding• Stereo and Multi-Camera Calibration and

Depth Computation• Mobile Robotics

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Who uses• license for OpenCV has been structured

such that you can build a commercial product using all or part of OpenCV.

• You are under no obligation to opensource

• large user community that includes people from major companies (IBM, Microsoft , Intel, SONY, Siemens, and Google, to name only a few) and research centers (such as Stanford, MIT, CMU, Cambridge, and INRIA).

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Using OpenCV

• Use static libraries• Compile OpenCV • Download sample from GITHUB

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Basic Structtypedef struct _IplImage

{

int nSize;int ID;int nChannels;int alphaChannel;int depth;

char colorModel[4];

char channel

int dataOrder;

int origin;

int align;

int width;int height;

struct _IplROI *roi;

struct _IplImage *maskROI;

void *imageId;

struct _IplTileInfo *tileInf

int imageSize;

char *imageData;

int widthStep;

char *imageDataOrigin;

}

IplImage;

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Some Code...

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Image inversion sample

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Erosion

• Characteristics of Erosion • Erosion generally decreases the sizes of objects and removes

small anomalies by subtracting objects with a radius smaller than the structuring element.

• With grayscale images, erosion reduces the brightness (and therefore the size) of bright objects on a dark background by taking the neighborhood minimum when passing the structuring element over the image.

• With binary images, erosion completely removes objects smaller than the structuring element and removes perimeter pixels from larger image objects.

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cvErode

• void cvErode( const CvArr* src, CvArr* dst, IplConvKernel* element=NULL, int iterations=1 );

• If it is NULL, a 3×3 rectangular structuring element is used. iterationsNumber of times erosion is applied. The function cvErode erodes the source image using the specified structuring element that determines the shape of a pixel neighborhood over which the minimum is taken:

• dst=erode(src,element): dst(x,y)=min((x',y') in element))src(x+x',y+y') The function supports the in-place mode. Erosion can be applied several (iterations) times. In case of color image each channel is processed independently.

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Dilation

• Characteristics of Dilation • Dilation generally increases the sizes of objects, filling in

holes and broken areas, and connecting areas that are separated by spaces smaller than the size of the structuring element.

• With grayscale images, dilation increases the brightness of objects by taking the neighborhood maximum when passing the structuring element over the image.

• With binary images, dilation connects areas that are separated by spaces smaller than the structuring element and adds pixels to the perimeter of each image object.

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Dilate• void cvDilate( const CvArr* src, CvArr* dst, IplConvKernel*

element=NULL, int iterations=1 ); • If it is NULL, a 3×3 rectangular structuring element is used.

iterationsNumber of times erosion is applied. The function cvDilate dilates the source image using the specified structuring element that determines the shape of a pixel neighborhood over which the maximum is taken:

• dst=dilate(src,element): dst(x,y)=max((x',y') in element))src(x+x',y+y') The function supports the in-place mode. Dilation can be applied several (iterations) times. In case of color image each channel is processed independently.

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Edge Detection (Canny Algorithm)

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FaceDetection

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Resources

• Download Open CV - http://sourceforge.net/projects/opencvlibrary/

• Install guide and tutorials - http://opencv.willowgarage.com/wiki/

• IDE – eclipse, .net , VC++

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• Questions?

Thanks