Course Content
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