Stereo Depth Estimation : Python/OpenCV2 C++/DirectX11
Colab Link : https://colab.research.google.com/drive/1Ey4mfWyh3wSpEplk6TY8eJepNdbtIoJn?usp=sharing
Showcase Video Of Point Cloud Visualizer
[Note : This was a group project of 5. The techniques noted below are my personal contributions towards the project]
Features
- Implemented Morphological transforms such as Hit or Miss transform, Erosion, Dilation, Opening, Closing, Template Matching.
- Added several edge detection algorithms such as Sorbel edge detectors, Laplacian edge detectors, and Unsharp masking.
- Disparity/Depth map generation by extracting relevant camera calibration data.
- Implemented segmentation algorithms such as WaterShed segmentation and Colour space segmentation (HSV).
- For pre-processing of images, implemented frequency domain filters such as Butterworth’s low/high pass filter, Ideal low/high pass filter
- Created a C++/DirectX11 application to represent the depth map in form of a point cloud visualizer.
Spatial Domain Sharpening Filters
Source / Original Image
N4 Laplacian Mask / Sharpened Image
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N8 Laplacian Mask / Sharpened Image
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Sorbel Mask / Sharpened Image
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Unsharp Masking Mask / Sharpened Image
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Frequency Domain Blurring / Sharpening Filters
Ideal Low and High Pass Filter Masks
Application of Ideal Low and High Pass Filters
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Application of ButterWorth’s Low and High Pass Filters
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Other Image Processing Techniques
Color Space Segmentation (HSV)
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Homomorphic Transformations
Morphological Closing
Hit or Miss Transform (object to hit : The 2 wheeler Driver)
Template Matching
Disparity and Depth Map Generation
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