1 IntroductionToOpenCV

This video lecture deals with is Introduction to OpenCV and where to download OpenCV library files and also intro to the opencv.org website

2.Configuring OpenCV library to VisualStudio 2010

This is video lecture deals with how to configure the OpenCV library with the your favorite IDE Microsoft Visual Studio 2010.It also deals with how to set up system path for the dll files of OpenCV. Once configuring is over, a Hello World sort of application is executed to check all the settings is working fine or not?

3.Hello World Program in OpenCV

This program explains how to display an image on the screen with OpenCV library.

4.Video Capture

In this video we will learn how to load video from file as well as how to capture video from camera using opencv library

5.AccessingPixelData

In this lecture we learn how to access pixel data stored in Mat object for both grayscale as well as color images in OpenCV.

You can take the help of these documents for understanding this lecture

http://www.4shared.com/office/c_jPWYyRce/5Image_arrangments.html

http://www.4shared.com/file/vP6JcF3Vba/5AccessingPixelData.html

http://www.4shared.com/office/PVLuBLdwce/5Ways_of_accessing_pixel_infor.html

6.Mixing of Frames

In this video you will learn how to club the 2 frames, one from camera and one more from video file to form single frame and display it on the window

get the docs and c++ file from:

.http://www.4shared.com/file/l1sqCGsgce/6Mixing_of_Frames.html

http://www.4shared.com/file/AgFbwZ-0ba/6Mixing_of_Frames.html

• Category

7.RGB to HSV Conversion

In this video lecture we shall see how to convert image from 



one color model to other.Mainly from BGR to HSV and HSV 



to BGR

You can download the c++ file and docs from links below: 

http://www.4shared.com/office/-

JFshddXba/7Color_Models.html


http://www.4shared.com/file/fd_meQrGba/7RGB_to_HSV_Conversion.html

8.Image Enhancement technique

In this video you will learn spatial image enhancement techniques like power law or gamma and log transforms in using opencv library

you can download files from following link:

http://www.4shared.com/file/273jEW9gce/8Image_Enhancement_technique.html

http://www.4shared.com/office/SR82Obzzba/8RangeConversion.html

9.Histogram part 1

In this video we learn the concepts of histograms and how to draw it on the window usingopencv library.

the files can be downloaded from the following links:

http://www.4shared.com/office/AwkkE09gba/9HISTOGRAM.html

http://www.4shared.com/file/6l6gnaTcba/9histogramdraw.html

10.Histogram[part2] in opencv

In this video lecture you will learn the histogram functions available in opencv library and how to plot 2D histogram for an image

download the file files from following link:

http://www.4shared.com/file/pDg1oN4Yba/10calcHist.html

http://www.4shared.com/file/HslDyKsfba/10calcHistProgram.html

11.colored OBJECT detection

In this video you will learn how to detect the colored object for given hue in an image.



documents can be downloaded from:
http://www.4shared.com/office/5MewHl10ba/11Obj_detect.html

cpp file can be downloaded from:
http://www.4shared.com/file/kW2ZTN83ce/11colUndstd.html

12.connectedComponentAnalysis

In this video lecture you will learn how to use connected component analysis to discard smaller colored object from the colour detection output

docs available at:

http://www.4shared.com/office/kSravO_bce/12Connected_component_analysis.html

code available at:

http://www.4shared.com/file/KFNVsDlrce/12colUndstdCPP.html

Microsoft Kinect + OpenNI2 +NiTE2+OpenCV

This blog takes you through the steps necessary for installing Microsoft Kinect SDK, OpenNI, NiTE and OpenCV library and also configuring it with Microsoft Visual Studio 2010.

Steps to install Microsoft Kinect SDK

1.      Download the latest Microsoft Kinect SDK and Kinect Developer Toolkit from the Microsoft Website which is available free of cost.

http://www.microsoft.com/en-us/kinectforwindows/Develop/sdk-eula.aspx

2.      First install the Microsoft Kinect SDK by double clicking it and then try installing Kinect Developer Toolkit, both of  which get installed in C:Program Files(x86) (for 32 bit machine) or C:/Program Files (for 64 bit machine)

3.      Microsoft Kinect SDK has drivers and library files required for application development with Kinect, whereas Kinect Developer Toolkit has certain application which are already built by Microsoft, which can be used to test the Kinect setup and driver installation.

4.      Once installation is done. Go to control panelàuninstall programàpress k. you should see the following figure, which confirms that SDK’s are setup and good to go.

5.      If you have plan for developing application of Kinect with Microsoft SDK, then start with some good textbooks and forum from Microsoft, or else if you want go for open source library, then go to the next steps.

Steps to install OpenNI2 library

6.      OpenNI library is one such library which allow us to take Kinect to any other platform instead of windows, like linux/mac. This library provides API for accessing Kinect Depth sensing and color camera. If you want access other peripherals like accelerometer, tilt motor and microphone array, well this is not the right choice. You need to continue with Microsoft Kinect SDK only.

7.      In this tutorial, I have installed the OpenNI version 2(or OpenNI2) in my windows 8 system.

8.      Download the library file from following website (choose library properly by appropriately choosing for 32 or 64 bit.)

http://structure.io/openni

Also you can download documentation from the same website.

One more link:

OpenNi 32 bit ~ https://drive.google.com/file/d/0B3e4_6C5_YOjMS1EQWh6VFhWbnc/edit?usp=sharing
OpenNi 64 bit ~ https://drive.google.com/file/d/0B3e4_6C5_YOjYmVPQzhwazhBOUE/edit?usp=sharing

9.      Install OpenNI2 library.

Steps to install NiTE library

10.  Download NiTE2 library from following link

Nite 32 bit ~ https://drive.google.com/file/d/0B3e4_6C5_YOjQWtCcVl3VnRsWG8/edit?usp=sharing
Nite 64 bit ~https://drive.google.com/file/d/0B3e4_6C5_YOjOGIySEluYkNibEE/edit?usp=sharing

11.  Install the NiTE2 library.

Steps to install OpenCV library

12.  For windows, installation is very easy. The version that I used was OpenCV2.4.9.

13.  Download the file from following website.

http://opencv.org/downloads.html

14.  Once downloaded, double click it to install and choose your hard disk space to get it install.

15.  For Linux, see the following blog.(For Ubuntu and Fedora)

http://kinishri6.blogspot.in/

Steps to configure our famous IDE Microsoft Visual Studio(MVS)

16.  I have done this configuration using MVS2010.This configuration remains same for all future MVS’s.

17.  Choose Debug or Release mode and set up for either x64 or x86

18.  Go to Projectàyour_project_name propertiesàConfiguration Properties

19.  Choose dropdown of C/C++

a.       In General TabàAdditional Include Directoreis

Add path for all the header files

In my case:(separated by “;” for each header file)

1)      for OpenCV-2.4.9

      G:\OpenCVProjects\opencv\build\include

2)      for NiTE2

C:\Program Files\PrimeSense\NiTE2\Include

3)      for OpenNI2

C:\Program Files\OpenNI2\Include

20.  Now choose Linker.

a.       In General TabàAdditional Library Directories,

Add the following path (In my case) (separated by “;” for each library)

1)      C:\Program Files\OpenNI2\Lib

2)      C:\Program Files\PrimeSense\NiTE2\Lib

3)      G:\OpenCVProjects\opencv\build\x64\vc10\lib (for 64 bit) or G:\OpenCVProjects\opencv\build\x86\vc10\lib (for 32 bit)

4)      $(OutDir)

b.      In Library TabàAdditional Dependencies,

Add the following library(separated by “;” for each library)(for Release mode)

NiTE2.lib;OpenNI2.lib;opencv_core249.lib;opencv_imgproc249.lib;opencv_highgui249.lib;opencv_ml249.lib;opencv_video249.lib;opencv_features2d249.lib;opencv_calib3d249.lib;opencv_objdetect249.lib;opencv_contrib249.lib;opencv_legacy249.lib;opencv_flann249.lib;opencv_gpu249.lib;opencv_nonfree249.lib;opencv_ocl249.lib;opencv_photo249.lib;opencv_videostab249.lib;opencv_stitching249.lib;opencv_superres249.lib;opencv_ts249.lib

21.  This finishes the configuration.

How to install OpenCV in FEDORA OS

In this post you will learn how to install OpenCV in your Fedora OS. This post is experimented in Fedora 20.

Requirements:

•  Internet connection
• FEDORA with latest updates running on your system.
•  Manually downloaded latest opencv zipped file for linux from opencv website.(We will not download through Terminal utility).

Procedures:

1.   Open the Terminal app
2.  go to Desktop using cd Desktop command
3. Let us install the Dependencies

     sudo yum install cmake pkgconfig gtk2 gcc gcc-c++

          (this will install basic packages required for opencv to run)

    4. Now we will install ffmpeg package(one more extra package)

sudo rpm -Uvh http://download1.rpmfusion.org/free/fedora/rpmfusion-free-release-stable.noarch.rpm http://download1.rpmfusion.org/nonfree/fedora/rpmfusion-nonfree-release-stable.noarch.rpm

type the following          

  sudo yum –y install ffmpeg

   5. So far, we have installed all the basic packages required

   6. Create a folder known as “OpenCV” in your desktop using GUI and                                    mouse+rightclick+create_new_folder

   7. Copy the zipped opencv file inside the “OpenCV” folder using mouse or keyboard

   8. Right click on the file and extract it. Once extract is done you should be able to                notice a directory “opencv-2.4.x”, where x is the version of opencv that you have          downloaded.

   9. Create a folder named “build” inside “opencv-2.4.x” directory

(From step 6 to 9, we could have done these steps through terminal but to simplify your life we made use of GUI,mouse and keyboard)

   10. Now in terminal

           cd opencv-2.4.x/build

 11. Now we will build the opencv and install it using cmake tool that you installed in             3rd step and make tool

  12. Run the following commands

               cmake –D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local –D WITH_TBB=ON -D WITH_EIGEN=ON ..

     (don’t miss the two dots)

               make

     (This will take little time to generate build of opencv. Once it finishes to 100%, run the following command)

              sudo make install

          (this will install opencv library in /usr/local directory)

        13. Once the installation is done we need to inform certain utility that opencv is                      available in the system for linking. One such utility we use is “pkg-config”

        14.  Open new file “opencv.conf” using vi editor

                 sudo /etc/ld.so.conf.d/opencv.conf

      add this statement in the file(press “i” to get insert mode of vi)

                                        /usr/local/lib

            once done press ESC, then :wq for saving the new created file opencv.conf and exit from vi editor

       15. Then type  sudo ldconfig in terminal

         16. Then type sudo vi /etc/profile

      add the following line in the file(press “i” to get insert mode of vi)

                 export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig

                 export LD_LIBRARY_PATH=/usr/local/lib

              once done press ESC, then :wq for saving the new created file opencv.conf and            exit from vi editor

        17.type source /etc/profile

Thus we have finished configuring part.So now you have configured pkg-config utility

 to identify the opencv . 

Now let us run a small program to check the opencv installation

• save this code in a file with name as "abc.cpp"

• change the path of the image in imread command with your own image available in hard disk(do not use this \, use only /, to separate directories) 

• to compile it 

 #include<opencv2/highgui/highgui.hpp>

using namespace cv ;

 int main()

{

     Mat img = imread("/home/USER/Pictures/python.jpg",CV_LOAD_IMAGE_COLOR);

     imshow("opencvtest",img);

     waitKey(0);

     return 0;

}

• g++ 'pkg-config --cflags opencv' abc.cpp 'pkg-config --libs opencv' -o abc 

• which generates executable named as "abc", now run the abc
• ./abc

By now you must see your image being loaded up in a window
Thus, OpenCV is properly configured in your Linux system
Note: Never ever forget to add header files as shown above in the code(dont miss "opencv2/")
Other header file available in OpenCV are as follows

#include "opencv2/core/core_c.h"
#include "opencv2/core/core.hpp"
#include "opencv2/flann/miniflann.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/photo/photo.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/ml/ml.hpp"
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib/contrib.hpp"

or simply add #include "opencv2/opencv.hpp" which includes all the header file mentioned above