Quality inspection of aluminum foil products plays an important role for aluminum foil manufactures. We present a method that uses input estimate (IE)-based chi-square detectors for defect detection in aluminum foil. It is assumed that the intensity of the aluminum foil image is Gaussian distributed, and the distribution of the defect intensity is different from the normal. Under these assumptions, Kalman filters with a constant velocity (CV) model are used to filter the image. We assume there is an unknown input in the CV model and the unknown input is estimated in the filtering process. The defects are determined by the chi-square test of the estimate of the unknown input. Experiments show that our technique is effective for most defects in aluminum foil.