In a 3D environment, when a 2D figure is photographed from different camera angles, the pictures have a relation that approximates an affine transformation. Detecting an affine transformation is an important problem in the area of computer vision. The log-polar transform is known to be a model of the central-fovea visual sensor in a creature's vision. One study described a method to detect the affine parameter by using a log-polar transform; however, this transform is not invariant to object position, so it is necessary to find beforehand the corresponding characteristic point. In this study, a new log-polar transform method which is invariant to object position change and affine transform is described. One amplitude feature in the frequency domain, the orientation of the 2D figure is retained but change of position is not retained, so the orientation can be detected regardless of the position of the figure. By combination with edge extraction, the affine parameter can be detected with little effect by a background change.