Depth perception starts with the binocular interaction receptive fields of simple cells modeled by two Gabor functions followed by a half-squaring function. Simple cells do not have reliable disparity computation. Complex cells combine two simple cells in quadrature. They are better adapted to encode disparity information. The image disparity can be determined by fixing the receptive field in one eye and varying it in the other. Pooling information of spatial frequency and orientation is very important to improve the quality of results of real world stereograms. In this work, a bio-inspired method to calculate binocular disparity based on the energy model for depth perception of real world images is described and implemented. The performance of the proposed method is also evaluated in what concerns the algorithm computational cost, root-mean-square error and percentage of wrongly matched pixels.