Automatic Hybrid Genetic Algorithm Based Printed Circuit Board Inspection

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 proposed framework allows novel composition of tasks such as edge-detection and thresholding in order to increase defect detection accuracy with low computational time. Our simulations on real PCB images demonstrate that the HGA is robust enough to detect a...

• Type: Conference
• Year: 2006
• Where: AHS
• Authors: Syamsiah Mashohor, Jonathan R. Evans, Ahmet T. Erdogan
• Keywords: AHS 2006, Computational Time, Image Processing, Image Processing Algorithm