A Wavelet Analysis and Fast Fourier Transform-Based Defect Detection Method for Cigarette Package Aluminum Foil

Given the critical role of aluminum foil integrity in cigarette packaging for product quality assurance, this study proposes a defect detection methodology for cigarette package aluminum foil by integrating wavelet analysis and Fast Fourier Transform (FFT). Wavelet analysis can effectively extract information from the signal and has excellent signal-to-noise separation function, and can perform noise reduction processing on the detected signal. The fast Fourier transform can generate a spectrogram to obtain specific frequencies and amplitudes. The detection signals were initially decomposed through wavelet transform to eliminate high-frequency noise components, followed by application of FFT to the denoised signals for systematic analysis of their spectral characteristics. The combination of these two methods accurately detects defects in the aluminum foil paper of cigarette boxes.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1145/3756423.3756575
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

A Wavelet Analysis and Fast Fourier Transform-Based Defect Detection Method for Cigarette Package Aluminum Foil

Shengli Zhang, Yongdian Tong, Xiangyang Shi, Lei Yang et al.
Industrial Vision Systems and Defect Detection
article

A Wavelet Analysis and Fast Fourier Transform-Based Defect Detection Method for Cigarette Package Aluminum Foil

Shengli Zhang, Yongdian Tong, Xiangyang Shi, Lei Yang, Yongqi Wang, Qi Zhao, Yijian Liu, Junjun Xie, Pingli Mu
article en

Abstract

Given the critical role of aluminum foil integrity in cigarette packaging for product quality assurance, this study proposes a defect detection methodology for cigarette package aluminum foil by integrating wavelet analysis and Fast Fourier Transform (FFT). Wavelet analysis can effectively extract information from the signal and has excellent signal-to-noise separation function, and can perform noise reduction processing on the detected signal. The fast Fourier transform can generate a spectrogram to obtain specific frequencies and amplitudes. The detection signals were initially decomposed through wavelet transform to eliminate high-frequency noise components, followed by application of FFT to the denoised signals for systematic analysis of their spectral characteristics. The combination of these two methods accurately detects defects in the aluminum foil paper of cigarette boxes.

China Tobacco (CN), Zhengzhou University (CN), Henan University of Engineering (CN)
Openalex Percentile: Top 65%
Industrial Vision Systems and Defect Detection
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A Wavelet Analysis and Fast Fourier Transform-Based Defect Detection Method for Cigarette Package Aluminum Foil — Shengli Zhang, Yongdian Tong, et al. · (2025) | TGRS Research Map | TGRS