An LCS-based 2D Fragmented Image Reassembly Algorithm

Abstract

We propose an algorithm for 2D image fragment reassembly problem based on solving a variation of Longest Common Subsequence (LCS) problem. Our processing pipeline has three steps. First, the boundary of each fragment is extracted automatically from its scanned image, with paper tissue and scanning artifacts removed. Second, inter-fragment boundary matching is computed between each pair of fragments by solving a Longest Common Subsequence problem. The goal is to identify the best possible adjacency relationship among image fragment pairs. Finally, a multi-piece alignment is used to prune incorrect matches and globally compose the final image. We perform experiments on various image fragment datasets and compare our results with existing methods to show the improved efficiency and robustness with respect to images of different resolutions and different levels of noise on boundary pixels.