This project provides a comprehensive approach for verifying medical documents using advanced techniques in template extraction, comparison, and fraud detection.
- Region-of-Interest (ROI) Methods: Utilizes sophisticated techniques for precise extraction.
- Contour Analysis and Edge Detection: Enhances the clarity of templates.
- Pre-processing: Includes morphological operations and adaptive thresholding.
- Feature Matching: Utilizes key points and descriptors.
- Histogram-Based Analysis: Improves robustness by accounting for variations.
- Structural Similarity Index (SSIM): Quantifies structural similarity to identify potential matches.
- Optical Character Recognition (OCR): Extracts critical information such as patient details, provider information, and billing amounts.
- Data Comparison: Compares extracted information with a reference dataset.
- Confidence Thresholding: Ensures reliable fraud detection.
- Dynamic Adjustments: System parameters adapt to varying document layouts and structures.
This methodology ensures a robust and adaptable approach to medical document verification, effectively addressing the complexities of template extraction, comparison, fraud detection, and document structure variability.