GitHub - UtpalKuma-r/Image-Processing-Computer-Vision: Hands-on implementations of fundamental and advanced image processing techniques, ranging from image transformations, filtering, segmentation, feature detection, to object and face recognition. Each experiment is coded in Python and demonstrates key concepts essential for understanding computer vision applications.

List of Experiments

Simulation and display of an Image, Negative of an Image (Binary & Gray Scale)
Implementation of the Transformation of an Image.
Implementation of Histogram, and Histogram Equalization.
Implement the different filtering techniques for noise removal based on spatial and frequency domains using OpenCV.
Implementation of various image segmentation techniques. (Edge-Based, Region-Based and Threshold-Based)
Implementation of different Morphological Image Processing Techniques

Make sure you have the following installed before running the code:

To install OpenCV, run the following command:

pip install opencv-python

Name		Name	Last commit message	Last commit date
Latest commit History 16 Commits
experiment1		experiment1
images		images
output		output
README.md		README.md
expe2.py		expe2.py
expe3.py		expe3.py
expe4.py		expe4.py
expe5.py		expe5.py
expe6.py		expe6.py