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Computer Vision / Image Processing

  

Foundational Topics

  • Introduction to Image Processing
    • Image representation: pixels, channels
    • Color models (RGB, HSV, Grayscale, etc.)
  • Image Filtering
    • Convolution and kernels
    • Gaussian blur, sharpening, edge detection (Sobel, Canny)
  • Histogram Processing
    • Histogram equalization
    • Contrast stretching
  • Image Transformations
    • Scaling, rotation, translation
    • Affine and perspective transformations
  • Thresholding and Binarization
    • Global & adaptive thresholding
    • Otsu’s method

Intermediate Topics

  • Feature Detection and Matching
    • Harris corners, FAST, SIFT, SURF, ORB
  • Image Segmentation
    • Region-based, edge-based, clustering (e.g., k-means)
    • Watershed algorithm
  • Morphological Operations
    • Erosion, dilation, opening, closing
  • Object Detection (Classical Methods)
    • HOG + SVM
    • Viola-Jones face detection
  • Geometric Vision
    • Camera models, intrinsic/extrinsic parameters
    • Epipolar geometry, triangulation

Deep Learning in Vision

  • Convolutional Neural Networks (CNNs)
    • CNN layers and architectures (e.g., LeNet, VGG, ResNet)
  • Image Classification
    • Using CNNs for multi-class classification
  • Object Detection
    • R-CNN, Fast R-CNN, Faster R-CNN
    • YOLO (You Only Look Once), SSD
  • Semantic and Instance Segmentation
    • Fully Convolutional Networks (FCNs)
    • U-Net, Mask R-CNN
  • Image Generation
    • Autoencoders
    • GANs (Generative Adversarial Networks)
  • Image Captioning
    • Vision + NLP with encoder-decoder models

Advanced Topics & Applications

  • 3D Vision
    • Stereo vision, depth estimation
    • Structure from motion (SfM)
  • Optical Flow and Motion Estimation
  • Facial Recognition and Biometrics
  • Pose Estimation
    • OpenPose, MediaPipe
  • Augmented Reality (AR)
  • Visual SLAM (Simultaneous Localization and Mapping)
  • Medical Image Analysis
  • Remote Sensing & Satellite Imaging
  • Vision Transformers (ViT)

Practical Tools & Libraries

  • OpenCV
  • scikit-image
  • PIL/Pillow
  • TensorFlow/Keras, PyTorch (for deep learning)
  • Detectron2, MMDetection
  • Labeling tools (e.g., LabelImg, CVAT)

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