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Globally consistent reconstruction of ripped-up documents.

Liangjia Zhu¹, Zongtan Zhou, Dewen Hu

¹Department of Automatic Control, College of Mechatronics and Automation, National University of Defense Technology, People's Republic of China. ljzhu@nudt.edu.cn

IEEE Transactions on Pattern Analysis and Machine Intelligence

|November 15, 2007

Summary

This study presents a novel computational framework for automatically reconstructing ripped-up documents. It uses curve matching and a relaxation process to achieve globally consistent solutions for document fragment assembly.

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Area of Science:

Computer Vision
Computational Geometry
Digital Forensics

Background:

Automatic document reconstruction from fragments is challenging due to ambiguous matches.
Existing methods often rely on application-specific features, limiting generalizability.

Purpose of the Study:

To develop a general computational framework for reconstructing ripped-up documents.
To address the problem of finding globally consistent solutions from ambiguous fragment matches.

Main Methods:

Candidate matches are identified using curve matching between document fragments.
A relaxation scheme is employed to disambiguate candidate matches.
Global consistency is defined and optimized using an iterative gradient projection method.

Main Results:

The proposed approach effectively disambiguates candidate matches for document reconstruction.
Global consistency is achieved through iterative confidence updates.
Successful reconstruction of documents with up to fifty pieces was demonstrated.

Conclusions:

The developed global approach provides a sound method for automatic document reconstruction.
The framework offers a general solution without requiring application-specific features.
This method shows promise for practical applications in document recovery.