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16 October 2023 FTIDB: a new flue-cured tobacco leaf image database
Suxiao Li, Chao Guo, Xiaofang Zhang, Huanju Zhen, Gaili Wang, Huiwei Niu
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Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128031T (2023) https://doi.org/10.1117/12.3009578
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China
Abstract
The classification and grading of flue-cured tobacco leaf is an essential step in tobacco production. In order to carry out relevant research, a new flue-cured tobacco leaf image database (FTIDB) is established to provide high-quality and annotated flue-cured tobacco leaf image data. At present, the database consists of 2,113 flue-cured tobacco leaf images from major production regions across China. To ensure the quality of the database, a series of procedures are implemented. Firstly, the image acquisition system was constructed and the acquisition environment was calibrated. Secondly, Image pre-processing was adopted to improve the image quality. Thirdly, according to the characteristics and application requirements of tobacco leaf image, the image quality was objectively evaluated through quantitative metrics in terms of color, texture and greyscale. Fourthly, XML file was used to organize annotated information from tobacco experts. Finally, the image data dictionary was created to complete the data storage management using Microsoft Structured Query Language Server. This database can provide basic tobacco image resources for researchers and agricultural technicians, so that extensive studies can be performed and the automatic level of tobacco classification and grading will increase effectively.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Suxiao Li, Chao Guo, Xiaofang Zhang, Huanju Zhen, Gaili Wang, and Huiwei Niu "FTIDB: a new flue-cured tobacco leaf image database", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128031T (16 October 2023); https://doi.org/10.1117/12.3009578
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KEYWORDS
Image quality
Databases
Image segmentation
Image processing
Image acquisition
Calibration
Image classification
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