Speed-up Method of Rotation Template Matching Based on Optimization of Manifold's Shape

Abstract

Machine vision technology is important because it is used for automated assembly or visual inspections in factories. Template matching is one of the general recognition methods used for this. But, this method need to match a large number of templates to detect rotated objects in an acquired image. Therefore, it creates computing time problems. We solve this problem by proposing fast matching method using “manifolds”. Here, “manifolds” means trajectories in the multi-dimensional space. They comprise continuous points that correspond to multiple images. Since, the computing time depends on the manifold's shape, the proposed method reduced it by optimizing the manifold's shape. Experimental results showed the method achieved a 92.5% recognition rate and a 236 msec processing time.