A New Method of Shredded Paper Image Restoration Based on Ant Colony Algorithm

For the restoration problem of shredded paper broken by shredder machines with the same marginal feature, a new method based on ant colony algorithm with classification is proposed in this paper. Firstly, shredded paper feature vector can be extracted by image space information. Secondly, the similar matrix and the marginal distance matrix are defined by the feature vector and left-right part image information respectively for every pieces of paper. At last, the original order of shredded paper can be ensured by ant colony algorithm depending on the minimum marginal distance sum among adjacent pieces of paper. For the stitching and restoration of large-scale broken pieces of paper without obvious marginal feature, the classification processing in this paper can greatly reduce the solution scale and improve the algorithm efficiency. The actual experimental result shows the good stability, efficiency and strong robustness of the algorithm.