Tobacco Impurities Detection with Deep Image Segmentation Method on Hyperspectral Imaging

Linruize Tang, Min Zhao, Shuaikai Shi, Jie Chen, Jinwei Li, Qiang Li, Rengang Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

The detection of impurities in tobacco raw materials is an important task, and the performance of detection algorithms directly affects the quality of tobacco products. The hyperspectral imaging system simultaneously captures the visible and near-infrared spectra containing rich spectral information that can accurately reflect material categories. In this paper, we propose a novel deep learning-based tobacco impurities detection method on hyperspectral data. It is a U-net like structure that progressively extracts multi-scale discriminant features and fuses them to find the impurities in the scene. Experiments conducted on the collected dataset show that the proposed segmentation model yields superior performance compared to other detection methods.

源语言英语
主期刊名Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350316728
DOI
出版状态已出版 - 2023
活动2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023 - Zhengzhou, Henan, 中国
期限: 14 11月 202317 11月 2023

出版系列

姓名Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

会议

会议2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
国家/地区中国
Zhengzhou, Henan
时期14/11/2317/11/23

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