Computer Vision(CV) is one of the de facto Artificial Intelligence technology that is present in many AI applications we come across.
"Process of discovering from images what is present in the world, where it is, and what it is doing!"
The use of computer vision techniques is prevalent in a wide variety of applications, including facial recognition, self-driving cars, augmented reality, and many others.
Traditional computer vision involves an in-depth analysis of the input and output. The in-depth analysis reveal what mathematically representable features can be extracted from an image and coupled with an efficient algorithm to produce the desired result.
I have implemented the following techniques in Python using Traditional CV techniques:
- 1. Basics of Image Processing
- 2. Smoothening and Edge Detection
- 3. Similitude Momentsg
- 4. MHI and MEI
- 5. Motion Tracking
- 6. Superpixel and NCC
- 7. Feature extraction and Interest Point detection
- 8. 2D to 3D Projection Calculation
- 9. Template Matching and KNN