A transformational approach to visual perception is presented in which image structure is encoded in the parameters of those transformations that produce an output maximally symmetric with the current input Results are presented for a computer program, dubbed SMART (Symmetry Maximizing Array using Random Transformations). SMART consists of a parallel away of independent symmetry detectors. Each detector attempts to find a transformation that maximizes the symmetry between the original and the transformed configuration The weighted output of the detectors is collated in a connection matrix, which summarizes the image structure and provides a continuously varying measure of relative symmetry. The program is applied to constrained and random arrays, Glass figures, and the detection of hidden symmetric targets. More general implications are briefly discussed.