Rigid image registration via column sparse optimisation for seal registration
Image registration is an essential and important process in seal identification. Rigid image registration in seal identification is known to be more suitable than elastic registration. The registration process is quite sensitive to outliers in matched feature point pairs. A novel method to take the matching outliers as data corrupted by ‘sample-specific’ error which can be modelled by a column sparse matrix is proposed. An optimisation problem is developed to describe this model. By solving the optimisation problem, corruption can be eliminated and the transformation model can be recovered simultaneously. An efficient algorithm called column sparse registration is given via the augmented Lagrange multiplier method. Experiments on real-world seal registration data demonstrate that the proposed method is robust to outliers among matched pairs and outperforms the state-of-the-art methods.
