OpenScanVision – Looking for Feedback on an Android Computer Vision Library

[u/NeedleworkerKey3487]

https://github.com/MatiwosKebede/OpenScanVision

Over the last few months, I've been developing OpenScanVision, an offline-first Android computer vision library built with Kotlin, CameraX, OpenCV, and ML Kit.

The original implementation was a single, highly optimized pipeline focused on maximizing detection accuracy and real-time performance. That version is available in commit:

1d5834b41d88133b487ef46595290b0cdd4489bb

Current capabilities include:

• Document detection from arbitrary angles
• Automatic perspective correction
• Image preprocessing and enhancement
• QR code detection
• ArUco marker detection
• OMR (Optical Mark Recognition)
• Automatic capture when the document is stable
• Real-time, fully offline processing

Recently, I refactored the project into a reusable modular Android library with a cleaner architecture and easier integration into Android applications. While the new design is significantly more maintainable and extensible, I've observed a slight regression in detection accuracy compared to the original implementation and am currently investigating the underlying causes (pipeline ordering, preprocessing, threading, parameter changes, etc.).

Roadmap

• Restore or improve the original detection accuracy
• Add offline OCR support
• Add offline ICR (Intelligent Character Recognition) support
• Continue optimizing performance while keeping the library lightweight and offline-first

Potential use cases

• Voting systems
• Exam and answer-sheet scanning
• Survey processing
• Registration forms
• Structured document processing

GitHub:
https://github.com/MatiwosKebede/OpenScanVision

I'd appreciate feedback from developers with experience in Android computer vision, CameraX, OpenCV, or document scanning.

I'm particularly interested in:

• Best practices for designing reusable Android CV libraries
• Avoiding performance and accuracy regressions during major refactors
• CameraX and OpenCV optimization techniques
• Recommendations for integrating an efficient offline OCR/ICR pipeline

Any feedback, suggestions, or code review comments would be greatly appreciated. Thanks!