In this paper, a synthesis procedure of cellular neural networks (CNNs) template design for edge detection is proposed. This method combines simulated annealing and particle swarm optimization (SA-PSO) to search template values. In the process of searching, annealing temperature is used to adjust kick probability and roulette is adopted to select global optimal replacement value. In this way, trapping into local optimum problems of PSO can be effectively avoided. Moreover, in order to guarantee stable outputs of CNNs, properties of CNN feedback template obtained in previous researches are used to constraint particle solution space. Simulation results show CNN templates designed by this method are efficiency in edge detection.