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Program for Harris Corner Detection with non-maximum Suppression, HOG Feature Extraction, Feature Comparison, Gaussian Noise and Smoothing.

License: MIT License

Jupyter Notebook 100.00%

corner-detection's Introduction

Corner Detection and HOG Feature Comparison

Objectives:

  1. Gaussian Noise and Smoothing
  2. Harris Corner Detection
  3. Non-maximum Suppression
  4. Corner Localization
  5. Extract Feature Vectors with HOG
  6. Feature Comparison

Interactively controlled parameters:

  • Variance for gaussian (scale)
  • Smoothing value for gaussian smoothing (filter size)
  • Neighborhood size for computing the correlation matrix
  • Weight of the trace in the Harris corner detection
  • Threshold value for non-maximum Suppression

Program was implemented using Python and OpenCV. Refer the report for further implementation details and instructions to run the code: View Report

Results:

  1. Corner Detection with implemented Harris corner detection function and OpenCV:
Implemented Harris Corner Detection OpenCV

  1. Corner Detection with Gaussian Noise (variance = 1) and Gaussian Smoothing (filter size = 15):
Implemented Harris Corner Detection OpenCV

  1. Feature Comparison with Features Extracted:
Image 1 Image 2

corner-detection's People

Contributors

chandnii7 avatar patelc52 avatar

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