Evaluation of an algorithm for finding a match of a distorted texture pattern in a large image database

Evaluation of an algorithm for finding a match for a random texture pattern in a large image database is presented. The algorithm was designed assuming that the random pattern may be subject to misregistration relative to its representation in the database and assuming that it may have missing parts. The potential applications involve authentication of legal documents, bank notes, or credit cards, where thin fibers are embedded randomly into the document medium during medium fabrication. The algorithm achieves image matching by a three-step hierarchical procedure, which starts by matching parts of fiber patterns while solving the misregistration problem and ends up by matching complete fiber patterns. Performance of the algorithm is studied both theoretically and experimentally. Theoretical analysis includes the study of the probability that two documents have the same pattern, and the probability of the algorithm establishing a wrong match, as well as the algorithm's performance in terms of processing time. Experiments involving over 250,000 trials using databases of synthetic documents, containing up to 100,000 documents, were used to confirm theoretical predictions. In addition, experiments involving a database containing real images were conducted in order to confirm that the algorithm has potential in real applications.