SEEDO.AI (SEcure Extraction and Data O.rganization with AI) is an integrated project utilizing computer vision and machine learning for automated data capture and organization. The system comprises three core modules:
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Attendance Tracking System: This module leverages OpenCV for facial recognition and real-time attendance tracking.
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Optical Character Recognition (OCR): This module employs TensorFlow to extract text from documents like employee bills and salary slips, enabling automatic data population.
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Car Plate Detection and Recognition: This module utilizes OpenCV and machine learning algorithms to identify and extract car license plate numbers.
Integration and Functionality: SEEDO.AI integrates these modules to process visual data (images/videos). The system categorizes and stores extracted information (attendance data, document text, car plate numbers) in a dedicated database.
Technologies: The project utilizes a combination of powerful technologies including:
- OpenCV: Open-source computer vision library for facial recognition, object detection, and image processing.
- TensorFlow: Open-source machine learning framework for building and deploying OCR models.
- Robotic Process Automation (RPA): Automates repetitive tasks, enhancing efficiency.
- Machine Learning Algorithms: Specialized algorithms for various tasks like car plate recognition.
Benefits: SEEDO.AI offers several advantages such as:
- Automated Data Capture: Eliminates manual data entry, reducing errors and saving time.
- Improved Data Accuracy: Reduces human error in data transcription.
- Enhanced Security: Securely stores and categorizes extracted data.
- Streamlined Workflows: Enables automation of data acquisition tasks in various applications.