Handwritten Character Recognition

11000 ~~12000~~

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Product Name: Handwritten Character Recognition System
Version: 1.0
Platform: Python 3.x
Hardware Requirements:
- Camera Module or Scanner (for capturing handwritten characters)
- Raspberry Pi, PC, or similar computing device
Software Requirements:
- Python 3.x
- OpenCV library for image processing
- TensorFlow/Keras or PyTorch (for character recognition model)
- Numpy library
- Flask (optional, for web interface)
Functional Requirements:
- Real-time image capture and character detection
- Recognition of handwritten characters
- Display of recognized text
- User-friendly interface for managing character recognition
Non-functional Requirements:
- High accuracy in character recognition
- Low latency in processing and text display
- Robustness and reliability in various writing styles and conditions
- Scalability for different languages and character sets

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Key Features:

Real-time Image Capture and Character Detection:
- The system captures images of handwritten text in real-time using a camera module or scanner.
- Handwritten characters are detected and segmented from the captured images.
Character Recognition:
- The system uses a pre-trained machine learning model to recognize individual characters from the segmented text.
- The recognition model is trained on a diverse dataset of handwritten characters to achieve high accuracy.
Text Display:
- The system converts recognized characters into digital text and displays the output.
- Recognized text can be displayed on a screen or through a web interface.
User Management:
- An administrative interface allows for managing recognition settings and adding new character sets.
- Users can view detailed information about the recognition process and results.