Improved seam carving using meta-heuristics algorithms combination

In this paper we propose a novel method to improve seam carving based on the method meta-heuristic algorithms combining simulated annealing (SA) and genetic algorithm (GA). SA is a single solution method which searches locally while GA belongs to population based algorithms that globally search to find the best answer. By this strategy, both speed and quality of the seam carving method can be increased simultaneously. First, SA is performed to find near optimum seams, which form initial population of GA. Then genetic algorithm develops this initial population to find optimum seam. Experimental results show that search for optimum seams by our proposed method successfully improves the retargeting results of seam carving.