This Repo Contain computer vision class tasks implementations. All Algorithms used in this repo are implemnted from scratch in python with some numpy low level functions for optimizing the speed

Tasks Summary => Check each task readme for detailed description.

• Additive Noise (Uniform, Salt & Pepper, Gaussian).
• Noise Filtering (Average, Mean, Gaussian).
• Edge Detection (Sobel, Prewitt, roberts, Canny).
• Image Histograms and Distribution Curves.
• Histogram Normalization.
• Histogram Equalization (Contrast Enhancement).

• Hough Lines.
• Hough Circles.
• Active Countour (PDF Energy Minimization).
• Morpholigical Geodesic Countour (Erosion, Dilation, LevelSets).

• Harris Corners.
• SIFT
  • Scale-space extrema detection.
    • Diffrence of Gaussian (DOG).
    • Local Extrema Detection.
  • Keypoints (selection from dog extremum)
    • Accurate Keypoint Localization.
    • Contrast Threshold.
    • Eliminating Edge Response (Principle Curvature Ratio).
  • Keypoint Orientation.
  • Descriptor Representation.
  • Features Matching.

• Global Thresholding

  • OTSU.
  • Optimal.
  • MultiLevel.

• Local Thresholding

  • OTSU.
  • Optimal.
  • MultiLevel.
  • Local Integral Image

• Image Segmentation

  • K-Means.
  • Region Growing.
  • Mean Shift.
  • Agglomerative Clustering.

• Face Detection.
• EigenFaces/ PCA
  • Image Compression.
  • Face Recognition.

• Mohamed Ahmed Abdelaziz
• Mohamed Khaled Galloul
• Mohamed Abdelkarem Seyam
• Ahmed Mohamed badra