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Inspired by human vision, retina-like imaging has the feature of rotation and scaling invariance, which is beneficial for target tracking and recognition. However, there is a limitation that the center of field of view (FOV) should match with the target centroid. Currently, there is no effective method to quantitatively estimate the effects from this mismatch. To solve the issue, a novel evaluation method is proposed by applying the log-polar transform and Fourier transform. Then reconstruct the target image by exchanging magnitude and phase information between the target image and its rotated or scaled counterpart. Using two current methods of digital image processing, scale-invariant feature transform (SIFT) and biaxial projection similarity analysis (BPS), as evaluation criteria, the proposed method performs efficiently for all eccentric angles. Simulation results show that for a specific target, the invariance of rotation and scaling works effectively for a value above 0.69.