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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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.

Details

Title
An Optimized Genetic Algorithm-Based Wavelet Image Fusion Technique for PCB Detection
Author
Zhang, Tongpo 1 ; Yin, Qingze 1 ; Li, Shibo 1 ; Guo, Tiantian 2 ; Fan, Ziyu 3   VIAFID ORCID Logo 

 School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai 201209, China; [email protected] (Q.Y.); [email protected] (S.L.) 
 Department of Internet of Things Engineering, Computing Science and Artificial Intelligence College, Suzhou City University, Suzhou 215004, China; [email protected] 
 Department of Engineering, Durham University, Durham DH1 3LE, UK; [email protected] 
First page
3217
Publication year
2025
Publication date
2025
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3181416353
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.