aiInternal Project
Product Matching System
Barcode and product matching system achieving 97% accuracy using Tesseract OCR and YOLO object detection.
Developed at ProManage
Lead Data Scientist
2020
Internal project - no public access
Screenshots
About This Project
Created a matching and detection system that pairs barcodes with their corresponding products using OCR and object detection technologies. The system uses Tesseract OCR for barcode text extraction and YOLO for product detection, enabling automated inventory verification and product-barcode validation in warehouse and retail environments.
Key Features
- Barcode detection and OCR text extraction with Tesseract
- YOLO-based product detection and classification
- Automated barcode-product matching and verification
- Batch processing for inventory audits
- Real-time scanning for warehouse operations
- Mismatch alerts and detailed reporting
Challenges & Solutions
- Handling damaged or partially visible barcodes
- Matching products across different angles and orientations
- Achieving high accuracy with diverse product catalogs
- Real-time processing for warehouse scanning workflows
Results & Impact
- 97% accuracy in barcode-product matching
- Automated inventory verification process
- Reduced manual checking time and human errors
Technologies Used
PythonOpenCVYOLOTesseract OCRDeep LearningDocker
Project Details
- Category
- ai
- My Role
- Lead Data Scientist
- Duration
- 4 months
- Year
- 2020
- Company
- ProManage
- Status
- Internal / Private
Internal Project
This project was developed for internal use at ProManage. Source code and live demo are not publicly available due to confidentiality.