We present a distributed spiking neuron network (SNN) for handling low-level visual perception in order to extract salient locations in robot camera images. We describe a new method which reduce the computional load of the whole system, stemming from our choices of architecture. We also describe a modeling of post-synaptic potential, which allows to quickly compute the contribution of a sum of incoming spikes to a neuron's membrane potential. The interests of this saliency extraction method, which differs from classical image processing, are also exposed.