https://github.com/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.
https://github.com/utpalkuma-r/image-processing-computer-vision
computervision edgedetection filtering histogramequalization image-processing imagesegmentation opencv python
Last synced: about 2 months ago
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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.
- Host: GitHub
- URL: https://github.com/utpalkuma-r/image-processing-computer-vision
- Owner: UtpalKuma-r
- Created: 2025-02-27T04:22:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-31T16:20:07.000Z (about 1 year ago)
- Last Synced: 2025-03-31T17:03:32.438Z (about 1 year ago)
- Topics: computervision, edgedetection, filtering, histogramequalization, image-processing, imagesegmentation, opencv, python
- Language: Python
- Homepage:
- Size: 620 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## 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
## Requirements
Make sure you have the following installed before running the code:
- Python (3.x recommended)
- OpenCV (`cv2` module)
### Installation
To install OpenCV, run the following command:
```bash
pip install opencv-python
```