Chaotic species based particle swarm optimization algorithms and its application in PCB components detection

An improved particle swarm optimizer using the notion of chaos and species is proposed for solving a template matching problem which is formulated as a multimodal optimization problem. Template matching is one of the image comparison techniques. This technique is widely applied to determine the existence, location and alignment of a component within a captured image in the printed circuit board (PCB) industry where 100% quality assurance is always required. In this research, an efficient auto detection method using a multiple templates matching technique for PCB components detection is described. The new approach using chaotic species based particle swarm optimization (SPSO) is applied to the multi-template matching (MTM) process. To test its performance, the proposed Chaotic SPSO based MTM algorithm is compared with other approaches by using real captured PCB images. The Chaotic SPSO based MTM method is proven to be superior to other methods in both efficiency and effectiveness.

► Novel chaotic species based particle swarm optimization (SPSO) Algorithm.
► Chaotic SPSO for multimodal optimization problem.
► The Chaotic SPSO is applied to the multi-template matching (MTM) process.
► Apply the Chaotic SPSO algorithm for PCB components inspection and fault detection.
► The Chaotic SPSO based MTM method is proven to be superior to other methods.