About Project

A leading Philippines financial services provider wanted an advanced ID Similarity Matching System. The software solution utilizes a combination of cutting-edge technologies, including OpenCV, Optical Character Recognition (OCR), Regular Expressions (RE), and Pandas, to provide a reliable and accurate platform for comparing and matching different types of identification (ID) proofs. The project addresses the challenges associated with accurately identifying similarities between diverse ID proofs, including passports, driver’s licenses, and national IDs while considering contextual information, regional variations, and the detection of fake IDs.

Web
Platform/OS
Finance
Category

Brief

Brainvire’s development team thoroughly understood the client’s requirements and provided an advanced ID Similarity Matching software solution. They utilized OpenCV to perform essential preprocessing tasks, implemented OCR using specialized libraries, such as Tesseract, to extract text from different textual elements on ID proofs, applied Regular Expressions (RE) to parse and extract specific patterns from the extracted text, and utilized Pandas to validate extracted attributes against predefined patterns or formats specific to each region.

Highlights

Team Brainvire developed and delivered a fully functional ID Similarity Matching System using advanced technologies for the client. The product perfectly reflected what the client envisioned and enabled them to provide improved services to their clientele and upscale their business.

Case Study

Features

Image Preprocessing: OpenCV and image transformations ensure consistent and optimal conditions for subsequent attribute extraction.

Optical Character Recognition (OCR): OCR enabled text extraction from different textual elements on ID proofs, such as names, addresses, dates, and other relevant textual attributes.

Text Parsing: Regular Expressions (RE) allowed text parsing and helped identify and extract specific patterns from the extracted text.

Pandas Data Validation: Validated extracted attributes and enriched attribute data with contextually derived information for accurate matching.