Evolutionary algorithm for PCB inspection

Article type: Research Article

Authors: Crispin, A.J.^{a; *} | Rankov, V.^b

Affiliations: [a] Department of Computing and Mathematics, Manchester Metropolitan University, John Dalton Building, Chester Street, Manchester, M1 5GD, UK | [b] Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK

Correspondence: [*] Corresponding author. E-mail: a.crispin@mmu.ac.uk

Abstract: An important inspection task in the automated assembly of printed circuit boards (PCBs) is that of detecting if all components have been placed correctly on the board. This paper describes a constrained evolutionary search based inspection technique for simultaneously detecting multiple component objects in a source image. The approach has the advantage that it does not rely on image alignment (registration) as do conventional optical inspection methods such as image subtraction. It is a template based search method which achieves speed and quality requirements by making use of an evolutionary algorithm and a simultaneous search for multiple objects in a source image using a generalised template. The generalised template matching method defines a template model that takes into account the statistical variations between the grey-level appearances of components. The evolutionary search for specific components is constrained to Canny edges making this a fast method for locating multiple targets. Results are presented for locating multiple surface mount resistors on a PCB so that missing components can be reported.

Keywords: Evolutionary algorithm, pattern recognition, computer vision, circuit inspection

DOI: 10.3233/KES-2009-0177

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 13, no. 3-4, pp. 91-101, 2009