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Zhu Yakun, Mei Jifan, Guo Wenmeng, et al. Cigarette brand identification model based on PPF projection algorithm and hyperspectral technology[J]. Journal of Light Industry.

Citation:Zhu Yakun, Mei Jifan, Guo Wenmeng, et al. Cigarette brand identification model based on PPF projection algorithm and hyperspectral technology[J]. Journal of Light Industry. shu

Cigarette brand identification model based on PPF projection algorithm and hyperspectral technology

1. Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China;
2. Technology Center, China Tobacco Chongqing Industrial Co., Ltd., Chongqing 400000, China;
3. Xiangcheng Branch of Xuchang Tobacco Company, Xuchang 461700, China

Received Date:2023-10-12
Accepted Date:2023-12-28

Abstract

Addressing the complexity of cigarette ingredients and the challenges in brand identification, a cigarette brand identification model based on Projection Pursuit based on Fisher Criterion (PPF) and hyperspectral technology was proposed. Firstly, the PPF projection algorithm was employed to conduct spectral separability analysis on the original spectra as well as those processed with Multiplicative Scatter Correction (MSC), first-order derivative (1 ^stD), and second-order derivative (2 ^ndD). Secondly, feature wavelength selection was carried out using Successive Projections Algorithm (SPA) and Genetic Algorithm (GA) to enhance the classification performance in subsequent steps. Finally, cigarette brand identification models were established using Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms, enabling effective recognition of cigarette brands. The results indicate that, in the combination of hyperspectral technology and the PPF projection algorithm, the second-order derivative (2 ^ndD) serves as the optimal band processing method, significantly enhancing the spectral separability. The recognition model established based on 2 ^ndD-SPA-SVM emerges as the best model, achieving an overall classification accuracy of 94.58% and 92.50% for the training and test sets respectively. Moreover, a greater difference in the proportion of leaf silk and expanded silk among different brand formulations leads to a lower similarity value between categories and a higher recognition accuracy. This model can provide a new efficient, fast, accurate, and non-destructive classification and discrimination method for cigarettes of different grades. It offered theoretical support for the application of hyperspectral technology in cigarette brand maintenance, tobacco blend formulation design, and other scenarios.
- PPF projection algorithm,
- hyperspectral technology,
- cigarette brand identification,
- similarity representation
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沈阳化工大学材料科学与工程学院沈阳 110142

Cigarette brand identification model based on PPF projection algorithm and hyperspectral technology

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