MATLAB Shredded Document Reconstruction Technology

To solve the reconstruction problem of systematically shredded documents, we developed optimal matching algorithms and Best-First search algorithms that effectively address image restoration for vertical-cut, horizontal-vertical-cut, and double-sided cross-cut shredded papers. The MATLAB implementation generates reconstructed images through programmed algorithms. Key innovations include a threshold selection algorithm for image segmentation based on the minimum accumulated error criterion of pixel pairs, and a novel image boundary detection method called Correlation Degree. The workflow progresses from proposing algorithmic principles and analyzing their feasibility and effectiveness to concrete implementation. Experimental validation ensured accuracy and stability, while theoretical research and existing literature analysis established a solid foundation. This research makes significant contributions to shredded document reconstruction and provides valuable insights for future studies. Implementation highlights: - Optimal matching algorithm utilizes grayscale correlation calculations between adjacent shred edges - Best-First search employs priority queues to optimize fragment sequencing - Threshold algorithm dynamically determines segmentation points by minimizing pixel-pair MSE - Correlation Degree boundary detection measures continuity using sliding window variance analysis - MATLAB functions include imread() for image input, edge() for boundary extraction, and corr2() for similarity assessment