abdelkoudos/OCR-for-Egypt-National-ID

# OCR for Egyptian National ID This repository contains three projects that focus on building end-to-end OCR pipelines for Egyptian National ID cards. Each project addresses a different component of the ID, combining computer vision, image preprocessing, segmentation, and deep learning models to achieve high recognition accuracy. ## Projects Overview ### 1. Categorical Field Classification - Classifies **gender, religion, and marital status** from segmented ID fields. - Uses separate CNN models for each field, addressing **class imbalance** with data augmentation and synthetic data generation. - Achieves approximatly 99% F1 scores across all components. ### 2. Serial Number Recognition - Extracts and recognizes the **ID serial number** (two letters + seven digits). - Employs **wavelet-based denoising, adaptive thresholding, and contour analysis** for segmentation. - Custom CNN models outperform pretrained OCR tools (Keras OCR, Tesseract) with >93% overall accuracy. ### 3. Back ID 14-Digit Recognition - End-to-end system for recognizing the **14-digit number** on the back of the ID. - Pipeline includes robust preprocessing, contour-based segmentation, and CNN classification. - Achieves >94% line-level accuracy after iterative dataset cleaning and retraining. ## Notes - Each project is located in its own folder with a dedicated README containing detailed methodology, experiments, and results. - Datasets used in these projects are **confidential** and cannot be shared.