Applying target maneuver onset detection algorithms to defects detection in aluminum foil

Quality inspection of aluminum foil products plays an important role for aluminum foil manufactures, but it is an arduous work for human. In our work, the target maneuver onset detection algorithms are applied to defect detection in aluminum foil images and the results are inspiring. It is assumed that the intensity of aluminum foil images is Gaussian distributed and the distribution of defect intensity is different from the normal. Under these assumptions Kalman filters with constant velocity (CV) model are used to filter defect images. During the filter process the maneuver onset detection algorithms are used to detect defects. The three maneuver onset detection algorithms, the measurement based chi-square detector (MR), the input estimate based chi-square detector (IE) and the input estimate based Gaussian significance detector (IEG) are tried respectively and the performance of the three algorithms are compared.