Assignment on Digital Image Processing University course
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Reading Raw image (.DNG) and extracting useful metadata
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White-balancing, adjusted to Bayer pattern ( 'RGGB', 'BGGR', 'GRBG', 'GBRG' )
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Nearest-neighbor interpolation - bilinear interpolation
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Space transforms ( Cam, XYZ, sRGB )
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Find image rotation angle of a text image, using its DFT and horizontal projection
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Image rotation implementation and white-padding
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Find the contours of a character contained in an image
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Create training dataset from given image
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Training - validation set split
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Train K-NN classification models
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Evaluate models using given test image
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Harris corner detector
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Local rotation-invariant pixel descriptor
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Descriptor matching
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RANSAC algorithm implementation
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Image Stitching
Make sure you have MATLAB installed on your system. This project was developed and tested using MATLAB R2019a.
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Download: Click on the "Clone or download" button on this repository and choose "Download ZIP." Alternatively, you can use Git to clone the repository.
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Extract: After downloading, extract the contents of the ZIP file to a location of your choice.
The project is organized into different sections, each addressing specific image processing tasks. To see the results, follow these steps:
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Navigate to the "Raw to RGB image transformation" folder.
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Run the demo scripts provided for each function
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Explore the results displayed in the MATLAB figures.
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Go to the "Optical Character Recognition" folder.
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Run the demo scripts for each OCR function
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Examine the output and visualizations in the MATLAB figures.
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Open the "Image Registration" folder.
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Execute the demo scripts for different tasks
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Review the stitched images and other relevant visualizations.