A collection of projects focused on advanced Computer Vision techniques, ranging from geometric transformations and image stitching to feature matching and object detection.
- Image Mosaicing & Stitching Implementation of automated image stitching to create seamless panoramas.
Key Features: Interest point detection (Harris Corner), descriptor matching, and RANSAC for homography estimation.
Tech Stack: Python, OpenCV, NumPy.
Files: image_mosaic_2_imgs.ipynb, image_mosaics_3_imgs.ipynb.
- Augmented Reality (AR) Fundamentals Exploration of camera calibration and 3D-to-2D projections to overlay virtual objects onto real-world scenes.
Key Features: Estimating camera intrinsics/extrinsics and rendering 3D wireframes over detected markers.
Files: AR.ipynb.
- Food Product Analysis & OCR Integration of computer vision into functional software for health tracking.
Key Features: Real-time barcode scanning and nutritional data extraction using EasyOCR.
Tech Stack: Flutter, Python, FastAPI.
Architectures: CNNs, Object Detection, and Seq2Seq models.
Libraries: OpenCV, EasyOCR, Matplotlib, NumPy.
Concepts: Feature Matching (SIFT/ORB), Homography, Image Filtering, and RAG architectures.
Software Engineering with a specialization in Artificial Intelligence and Machine Learning.
Deep coursework and projects completed through Alexandria University.
Abdelrahman Moataz El-Borgy | www.linkedin.com/in/abdelrahmann-elborgy