opencv pres

8/7/2019 OpenCV Pres

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OpenCV stands for Open Source ComputerVision Library

Includes over 500 functions implementingcomputer vision, image processing andgeneral purpose numeric algorithms.

Portable and very efficient (implemented in

C/C++) Absolutely free for academic and commercial

use Available at http://sourceforge.net/projects/opencvlibrary

What is OpenCV


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Computer Vision Market is large and continues to grow.There is no standard API (like OpenGL and DirectX ingraphics, or OpenSSL in cryptography), most of CV

software is of 3 kinds:

1. Research code (slow, unstable,independent/incompatible data types)

2. Very expensive commercial toolkits (like Halcon,

MATLAB+Simulink, )3. Specialized solutions bundled with hardware (Video

surveillance, Manufacturing control systems, Medicalequipment )

Why OpenCV?


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To develop a universal toolbox for research and

development in the field of Computer Vision.

Standard library would simplify development of

new applications and solutions much easier.

Special optimization for Intel Architectures.

Why OpenCV?


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Configuring MSVS .NET 2005


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The First Program using OpenCV


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1-23: The code is clear, short and cross-platform, no need to use with

MFC/GTK/QT/, cross-platform1-2. Include OpenCV headers first7. IplImageis OpenCV image type7, 19. Use cvLoadImageand cvSaveImagetoload/save an image in multiple formats:JPEG, JPEG2000, BMP, PNG, TIFF, PPM.

9. Use cvPointand otherconstructorfunctions to initialize simplestructures on fly.15. Use CV_IMAGE_ELEM macro toaccess image pixels16-18. Use cvRoundfor very fast

float->int conversion.20. Use cvNamedWindowt o create self-updating highgui window21. Use cvShowImageto display image inwindow22. Use cvWaitKeyt o get input from user

The Program Analysis Line by Line


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Library Architecture


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Reading/Writing images in several formats

(BMP, JPEG, TIFF, PxM, Sun Raster).

Creating windows and displaying images in it.

HighGUI windows remember their content

(no need to implement repainting callbacks).

Simple interaction facilities: trackbars, getting

input from keyboard and mouse.

Highgui Library


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#include "highgui.h"

#include "cv.h

//main programIplImage * image;

cvNamedWindow("exam", 1);

CvCapture * cap = cvCaptureFromCAM(0);

while(1)

{

image = cvQueryFrame(cap);CvScalar s;

for(int i=100;i


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Matrix and Image Arithmetical and

Logical Operations

Linear algebra, DFT/DCT, vector math

Dynamic structures

Drawing functions

XML I/O

Cxcore Library


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It is possible to draw different shapes in

an image (IplImage/CvMat):

Lines, Circles, Ellipses, Elliptic Arcs

Filled polygons or polygonal

contours

Text (using one of embedded fonts)

Everything can be drawn with different

colors, different line width.

Using CXCORE + HighGUI you can visualize everything


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Cv and Cvaux Libraries


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Image filters,

Morphology

Pyramids

Color space conversions

Geometrical transformations Histograms.

Basic Image Processing:


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Primitive operations:

cvErode(A,C,B); cvDilate(A,C,B);

Erosion:C(x,y)=minB(x,y)=1A(x+x,y+y)

Dilation:

C(x,y)=maxB(x,y)=1A(x+x,y+y)

Erode/Dilate Example


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Corner detection

Canny edge detector

Hough transform

Distance transform

Watershed

Inpainting

etc.

Advanced Image Processing and

Feature extraction


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Feature Extraction: Canny Edge Detector

Computing binary edge map from grayscale image: cvCanny(A,B,t1,t2);

Assisting object segmentation Accelerating face detection


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Image moments

Contours

Delaunay triangulation

Voronoi Diagram

Shape analysis and Computational geometry

Delaunay Triangulation


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Contours

In OpenCV contours are extracted from black-n-whiteimages. Outer or internal boundaries of white areasare stored as polygons:cvFindContours(bw, storage, &contours);contours=cvApproxPoly (contours, params);


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Optical flow

Object tracking (Meanshift& CAMSHIFT)

Motion templates

Kalman filters

Motion Analysis


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Motion Analysis and Object Tracking

Feature tracking: cvCalcOpticalFlowPyrLK

Color object tracking: cvCamShift

Motion templates: cvUpdateMotionHistory, cvCalcMotionGradient,

cvCalcGlobalOrientation, cvSegmentMotion


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Statistical classification

Regression

ClusteringAlgorithms: SVM, kNN, Normal

Bayesian classifier, Neural Nets

(MLP), Decision Trees, Random

Trees, Boosting, EM.

ML Library


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Thank you


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