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An Optimized Genetic Algorithm-Based Wavelet Image Fusion Technique for PCB Detection

Zhang, Tongpo; Yin, Qingze; Li, Shibo; Guo, Tiantian; Fan, Ziyu

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Authors

Tongpo Zhang

Qingze Yin

Shibo Li

Tiantian Guo

Profile image of Ziyu Fan

Ziyu Fan ziyu.fan@durham.ac.uk
Post Doctoral Research Associate



Abstract

This study proposes an optimized genetic algorithm-based wavelet image fusion technique for printed circuit board (PCB) detection, incorporating an improved Genetic Algorithm (GA) with the Elite Strategy and integrating it with discrete wavelet transform (DWT). The proposed method aims to enhance both the accuracy and efficiency of image fusion, which is crucial for defect detection in PCB inspection. A DWT is utilized to decompose images into multiple frequency components, where the low-frequency band preserves the structural integrity of the image, and the high-frequency band retains essential fine details such as edges and textures, which are critical for identifying defects. An improved genetic algorithm is applied to optimize the fusion process, incorporating the Elite Strategy to retain the best solutions in each evolutionary iteration. This strategy prevents the loss of optimal wavelet decomposition weights, and ensures steady convergence towards the global optimum. By maintaining superior solutions throughout the evolutionary process, the algorithm effectively enhances the fusion quality and computational efficiency. Experimental evaluations validate the effectiveness of the proposed approach, demonstrating superior performance over conventional fusion methods. The enhanced algorithm achieves significant improvements in key performance metrics, including relative standard deviation (RSD), peak signal-to-noise ratio (PSNR), image clarity, and processing efficiency. The team developed a prototype system and conducted simulations in a relatively realistic environment to validate the proposed method’s potential for high-precision PCB detection. The results demonstrate that the approach offers a robust solution for automated defect detection and quality assessment.

Citation

Zhang, T., Yin, Q., Li, S., Guo, T., & Fan, Z. (2025). An Optimized Genetic Algorithm-Based Wavelet Image Fusion Technique for PCB Detection. Applied Sciences, 15(6), Article 3217. https://doi.org/10.3390/app15063217

Journal Article Type Article
Acceptance Date Mar 13, 2025
Online Publication Date Mar 15, 2025
Publication Date Mar 2, 2025
Deposit Date May 28, 2025
Publicly Available Date May 28, 2025
Journal Applied Sciences
Electronic ISSN 2076-3417
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 15
Issue 6
Article Number 3217
DOI https://doi.org/10.3390/app15063217
Keywords genetic algorithm, image fusion, DWT, industrial inspection
Public URL https://durham-repository.worktribe.com/output/3789938

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