OCR-Based Task Listing from Handwritten Notes (Mobile App)

[rhasanm]

Title:

[Feature Request] OCR-Based Task Listing from Handwritten Notes (Mobile App)

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Description:

A feature to capture handwritten task lists from paper using the mobile app's camera, converting them into text format, and adding them to the app's task list. This would allow users to write task lists manually for convenience and have the app automatically recognize and digitize these tasks for further tracking or management.

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User Story

As a user, I want to take a picture of my handwritten task list, so I can quickly add tasks to the app without manually typing each task. This feature will improve productivity, allowing me to use the flexibility of pen and paper while keeping track of tasks digitally.

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Proposed Solution

1. Capture Image:

   • Use the mobile device's camera to take a photo of the handwritten task list.
   • The app should prompt users to align the paper properly for best OCR results.

2. OCR Processing:

   • Use OCR technology to recognize handwritten text from the captured image.
   • Integrate with a reliable OCR library, such as Tesseract or a third-party OCR API (e.g., Google Cloud Vision API or Microsoft Azure Computer Vision).

3. Text Parsing and Extraction:

   • Extract recognized text from the OCR output.
   • Parse the text to separate each task as an individual list item.
   • Allow users to edit the recognized text if OCR results need correction.

4. Task Creation:

   • Populate the extracted tasks into the app’s task list view.
   • Allow users to organize or edit tasks as needed before finalizing the list.

5. Save and Sync:

   • Save the list to the app’s task manager.
   • Sync the tasks with the user’s account if the app supports cloud sync.

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Acceptance Criteria

1. The mobile app should be able to capture a clear image of the handwritten notes.
2. The OCR system should accurately recognize handwritten text from various handwriting styles with an acceptable success rate.
3. Users should be able to review and edit tasks before adding them to the list.
4. The app should handle errors gracefully if OCR fails (e.g., low-quality image or unreadable handwriting).
5. Tasks are added to the digital list and saved within the app after user confirmation.

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Considerations

• Handwriting Variability: OCR may struggle with certain handwriting styles. Future improvements could include machine learning models trained on personalized handwriting styles.
• Language and Localization: Ensure OCR works for the user’s primary language.
• Privacy and Security: If using a cloud-based OCR API, consider privacy implications for sensitive information.
• User Feedback: After OCR processing, provide feedback to users on which parts of the text were recognized accurately and offer a quick editing option.

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Technical Specifications

• OCR Library/Service: (e.g., Tesseract, Google Cloud Vision, or Azure Computer Vision)
• Image Preprocessing: Enhance image quality before OCR (e.g., grayscale conversion, noise reduction).
• UI Elements:
  • Camera view with an alignment guide.
  • OCR review/edit screen with task preview before adding to the list.

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Additional Notes

This feature aims to enhance productivity by bridging the gap between traditional handwritten notes and digital task management. It provides users with a hybrid approach to task management, allowing them to work in the format they prefer while retaining the app's tracking and organization capabilities.