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Automatic Hybrid Genetic Algorithm Based Printed Circuit Board Inspection Syamsiah Mashohor, Jonathan R. Evans and Ahmet T. Erdogan
 

Summary: Automatic Hybrid Genetic Algorithm Based Printed Circuit Board Inspection
Syamsiah Mashohor, Jonathan R. Evans and Ahmet T. Erdogan
School of Engineering and Electronics
University of Edinburgh
Edinburgh EH9 3JL, Scotland, UK
Email: S.Mashohor@sms.ed.ac.uk, {Jonathan.Evans,Ahmet.Erdogan}@ee.ed.ac.uk
Abstract
The paper presents a novel integrated system in which
a number of image processing algorithm are embedded
within a Genetic Algorithm (GA) based framework in order
to provide an adaptation and better quality analysis with
less computational complexity while maintaining flexibility
to a broad range of defects. A specially tailored hybrid
GA (HGA) is used to estimate geometric transformation
of arbitrarily placed Printed Circuit Boards (PCBs) on a
conveyor belt without any prior information such as CAD
data. A library of image processing functions is accessed by
the HGA within an intelligent framework. These functions
include operations such as fixed multi-thresholding, Sobel
edge-detection, image subtraction and noise filters. The

  

Source: Arslan, Tughrul - School of Engineering and Electronics, University of Edinburgh

 

Collections: Engineering