basic-image-processing

In this project, we tried to implement multiple computer vision & image processing techniques, starting from the basic level of image manipulation to some advanced images segementation and texture analysis.

Setup and Run

• Clone the repository on your local machine
• Create a virtual environemnt and activate it:

 python3.8 -m venv venv
 . venv/bin/activate

• Install the dependencies using pip install -r requirements.txt

Code Structure

In this project, the code is structured into 4 main modules: fundamentals, frequency-filters-segmentation, image-segmentation, and texture-analysis.

fundamentals/

In this modules, we made some basic image manipulation like:

• Image loading
• Handling channels
• Converting between channels
• Thresholding
• Histogram & intensity transformations:
  • Negative transformation
  • Log transformation
  • Power-law transformation (gamma transformation)
  • Histogram equialization
• Calculating image contrast

frequency-filters-segmentation/

In this module, we did image segmentation using some frequency filtering techniques:

• Filter images using Fourier Transform
• Filter images using Wavelet Transform (also for image compression)
• Correct image using erosion and dilation

image-segmentation/

In this module, we implemented different image segmentation techniques, such as:

• Contour approach
  • Detecting edges using Sobel
• Region based segmentation
  • Thresholding/Otsu
  • Split-merge
  • Erosion & Dilation

texture-analysis/

In this module we tried some texture analysis techniques like:

• Cooccurence matrix
• LBP (Local Binary Patterns)

Final Words

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