Refinements of the energy expression of a real-time neural-based stereo vision system are presented. The neural network optimizes a scalar functional, that represents an area-based stereo matching algorithm. The neural system is reviewed and its performances presented. The proposed improvements are in terms of the exploitation of the image chromatic content and of local pixel information relative to the distance from an image feature. Experimental results showing the performance improvements are presented on synthetic and on real images. The hardware implementation currently in progress will straightforwardly benefit from these improvements.