This is the source code that summarizes the codes that I have gathered while attending Professor Sungho Kim's class (Yeungnam University, computer vision class) and my personal studies.
1. Install OpenCV 2. Camera Distortion 3. Color Space 4. Image Filtering 5. Edge 6. Corner and Blob detector 7. Fitting 8. Calibration 9. Stereo Matching and Rendering 10. Face and body detection
I installed OpenCV version(2.4.13.6)
Environment variables: C:\opencv24136\build\x86\vc14\bin;
VS Setting
Include Directories
C:\OpenCV24136\build\Include
Library Directories
C:\opencv24136\build\x86\vc14\lib
Additional Dependencies
opencv_calib3d2413d.lib;
opencv_contrib2413d.lib;
opencv_core2413d.lib;
opencv_features2d2413d.lib;
opencv_flann2413d.lib;
opencv_gpu2413d.lib;
opencv_highgui2413d.lib;
opencv_imgproc2413d.lib;
opencv_legacy2413d.lib;
opencv_ml2413d.lib;
opencv_nonfree2413d.lib;
opencv_objdetect2413d.lib;
opencv_ocl2413d.lib;
opencv_photo2413d.lib;
opencv_stitching2413d.lib;
opencv_superres2413d.lib;
opencv_ts2413d.lib;
opencv_video2413d.lib;
opencv_videostab2413d.lib;
Go 0. Outline
INPUT
OUTPUT
Go 0. Outline
INPUT
OUTPUT(Blue)
OUTPUT(Green)
OUTPUT(Red)
INPUT
OUTPUT(Blue)
OUTPUT(Green)
OUTPUT(Red)
INPUT
OUTPUT(Blue)
OUTPUT(Green)
OUTPUT(Red)
Builtin function vs Implementation (RGB to Gray)
INPUT
OUTPUT(Builtin)
OUTPUT(Implementation)
Builtin function vs Implementation (RGB to HSI)
INPUT
OUTPUT(Builtin-HSV)
OUTPUT(Implementation-HSI)
HSI(Hue, Saturation, Intensity) of Implementation
Builtin function vs Implementation (RGB to HSV)
INPUT
OUTPUT(Builtin-HSV)
OUTPUT(Implementation-HSV)
HSV(Hue, Saturation, Value) of Implementation
Go 0. Outline
Blur Result(Smoothed Image)
INPUT
OUTPUT(Kernel 1X1)
OUTPUT(Kernel 3X3)
OUTPUT(Kernel 5X5)
OUTPUT(Kernel 11X11)
OUTPUT(Kernel 19X19)
OUTPUT(Kernel 25X25)
OUTPUT(Kernel 29X29)
Salt & Pepper Result(Filtered Image Median vs Gaussian)
INPUT
OUTPUT(Salt&Pepper Noised)
OUTPUT(Median Filtered 1X1)
OUTPUT(Gaussian Filtered 1X1)
OUTPUT(Median Filtered 3X3)
OUTPUT(Gaussian Filtered 3X3)
OUTPUT(Median Filtered 5X5)
OUTPUT(Gaussian Filtered 5X5)
OUTPUT(Median Filtered 7X7)
OUTPUT(Gaussian Filtered 7X7)
OUTPUT(Median Filtered 9X9)
OUTPUT(Gaussian Filtered 9X9)
Salt & Pepper Result(Filtered Image Sigma of Gaussian)
OUTPUT(sigmaX, sigmaY = 1)
OUTPUT(sigmaX, sigmaY = 3)
OUTPUT(sigmaX, sigmaY = 5)
Gaussian Noised Result(Filtered Image Median vs Gaussian)
Gaussian Noise
Gaussian Kernel example
OUTPUT(Median Filtered 1X1)
OUTPUT(Gaussian Filtered 1X1)
INPUT
OUTPUT(Gaussian Noised)
OUTPUT(Median Filtered 1X1)
OUTPUT(Gaussian Filtered 1X1)
OUTPUT(Median Filtered 3X3)
OUTPUT(Gaussian Filtered 3X3)
OUTPUT(Median Filtered 5X5)
OUTPUT(Gaussian Filtered 5X5)
OUTPUT(Median Filtered 7X7)
OUTPUT(Gaussian Filtered 7X7)
OUTPUT(Median Filtered 9X9)
OUTPUT(Gaussian Filtered 9X9)
Gaussian Noised Result(Filtered Image Sigma of Gaussian)
OUTPUT(sigmaX, sigmaY = 1)
OUTPUT(sigmaX, sigmaY = 3)
OUTPUT(sigmaX, sigmaY = 5)
Go 0. Outline
INPUT
OUTPUT
Canny edge another Result
INPUT
OUTPUT(Min Threshold0)
OUTPUT(Min Threshold25)
OUTPUT(Min Threshold50)
OUTPUT(Min Threshold75)
OUTPUT(Min Threshold100)
X direction
Y direction
Magnitude(X+Y)
Direction(X,Y)
Go 0. Outline
6. Corner and Blob detector
Harris Corner Detector
Threshold LOW = Detected Corners MANY
INPUT
OUTPUT
INPUT
OUTPUT
Go 0. Outline
INPUT
OUTPUT(Object)
INPUT
OUTPUT(Scene)
OUTPUT(Good matches & Object detection)
Homography Estimation
Method(0, RANSAC, LMEDS) of fineHomography function
0(object)
RANSAC(object)
LMEDS(object)
0(Scene)
RANSAC(Scene)
LMEDS(Scene)
0(Good matches & Object detection)
RANSAC(Good matches & Object detection)
LMEDS(Good matches & Object detection)
Go 0. Outline
Pring Checkerboard
Using CamCalibrator tool of Darkpgmr
Check Calibrate and Calculate focal length of your camera
Go 0. Outline
9. Stereo Matching and Rendering
Block matching based Disparity
INPUT(Left)
INPUT(Right)
OUTPUT(Support 5)
OUTPUT(Support 7)
OUTPUT(Support 9)
OUTPUT(Support 11)
OUTPUT(Support 15)
OUTPUT(Support 17)
OUTPUT(Support 19)
OUTPUT(Support 21)
x,y,z
Depth Image
Result
0,0,140
56,0,140
-42,0,140
0,0,0
Texture mapping on the 3D shape
INPUT
OUTPUT(No move)
OUTPUT(move)
OUTPUT(inner)
Go 0. Outline
10. Face and body detection
INPUT
OUTPUT
Go 0. Outline
searching at google, matlab, nanhee kim's and sungho kim class
colorful stock corni_fructus earth
Nanhee Kim / @nh9k
