We address the problem of rejecting false matches of points between two perspective views. The two views are taken from two arbitrary, unknown positions and orientations. We present an algorithm for identification of the false matches between the views. The algorithm exploits the possibility of rotating one of the images to achieve some common behavior of the correct matches. Those matches that deviate from this common behavior turn out to be false matches. Our algorithm does not, in any way, use the image characteristics of the matched features. In particular, it avoids problems that cause the false matches in the first place. The algorithm works even in cases where the percentage of false matches is as high as 85 percent. The algorithm may be run as a post-processing step on output from any point matching algorithm. Use of the algorithm may significantly improve the ratio of correct matches to incorrect matches. We present the algorithm, identify the conditions under which it works, and present results of the test.