高光谱成像
分级(工程)
计算机科学
人工智能
模式识别(心理学)
样品(材料)
目视检查
图像质量
计算机视觉
工程类
图像(数学)
色谱法
土木工程
化学
作者
Lei Feng,Susu Zhu,Fei Liu,Yong He,Yidan Bao,Chu Zhang
出处
期刊:Plant Methods
[BioMed Central]
日期:2019-08-08
卷期号:15 (1): 91-91
被引量:198
标识
DOI:10.1186/s13007-019-0476-y
摘要
Hyperspectral imaging has attracted great attention as a non-destructive and fast method for seed quality and safety assessment in recent years. The capability of this technique for classification and grading, viability and vigor detection, damage (defect and fungus) detection, cleanness detection and seed composition determination is illustrated by presentation of applications in quality and safety determination of seed in this review. The summary of hyperspectral imaging technology for seed quality and safety inspection for each category is also presented, including the analyzed spectral range, sample varieties, sample status, sample numbers, features (spectral features, image features, feature extraction methods), signal mode and data analysis strategies. The successful application of hyperspectral imaging in seed quality and safety inspection proves that many routine seed inspection tasks can be facilitated with hyperspectral imaging.
科研通智能强力驱动
Strongly Powered by AbleSci AI