Artificial Intelligence

Course Content

Total learning: 10 lessons

Part – 6

 Image Processing / Computer Vision Using OpenCV

  • Understanding about Computer Vision related applications
  • Various challenges in handling Images and Videos
  • Images to Pixel using Gray Scale and Color images
  • Color Spaces – RGB, YUV, HSV
  • Image Transformations – Affine, Projective, Image Warping
  • Image Operations – Point, Local, Global
  • Image Translation, Rotation, Scaling
  • Image Filtering – Linear Filtering, Non-Linear Filtering, Sharpening Filters
  • Smoothing / Blurring Filters – Mean / Average Filters, Gaussian Filters
  • Embossing, Erosion, Dilation
  • Convolution vs Cross-correlation
  • Boundary Effects, Padding – Zero, Wrap, Clamp, Mirror
  • Template Matching and Orientation of image
  • Edge Detection Filters – Sobel, Laplacian, LoG (Laplacian of Gaussian)
  • Bilateral Filters
  • Canny Edge Detector, Non-maximum Suppression, Hysteresis Thresholding
  • Image Sampling – Sub-sampling, Down-sampling
  • Aliasing, Nyquist rate, Image pyramid
  • Image Up-sampling, Interpolation – Linear, Bilinear, Cubic
  • Detecting Face and eyes in the Video
  • Identifying the interest points, key points
  • Identifying corner points using Harris and Shi-Tomasi Corner Detector
  • Interest point detector algorithms
  • Reducing the size of images using Seam Carving
  • Contour Analysis, Shape Matching and Image segmentation
  • Object Tracking, Object Recognition
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