Objectives:
- Gaussian Noise and Smoothing
- Harris Corner Detection
- Non-maximum Suppression
- Corner Localization
- Extract Feature Vectors with HOG
- 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
- Corner Detection with implemented Harris corner detection function and OpenCV:
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| Implemented Harris Corner Detection | OpenCV |
- Corner Detection with Gaussian Noise (variance = 1) and Gaussian Smoothing (filter size = 15):
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| Implemented Harris Corner Detection | OpenCV |
- Feature Comparison with Features Extracted:
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| Image 1 | Image 2 |