Detection of early decay on citrus using LW-NIR hyperspectral reflectance imaging coupled with two-band ratio and improved watershed segmentation algorithm
文献类型： 外文期刊
作者： Tian, Xi 1 ; Zhang, Chi 1 ; Li, Jiangbo 1 ; Fan, Shuxiang 1 ; Yang, Yi 1 ; Huang, Wenqian 1 ;
作者机构： 1.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
2.Natl Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
关键词： Citrus; Decay detection; Band ratio image; Hyperspectral imaging; Near infrared; Improved watershed segmentation algorithm
期刊名称：FOOD CHEMISTRY （ 影响因子：7.514； 五年影响因子：7.516 ）
ISSN： 0308-8146
年卷期： 2021 年 360 卷
页码：
收录情况： SCI
摘要： Decay is a serious problem in citrus storage and transportation. However, the automatic detection of decayed citrus remains a problem. In this study, the long wavelength near-infrared (LW-NIR) hyperspectra reflectance images (1000-1850 nm) of oranges were obtained, and an effective method to detect decayed citrus was proposed. Three effective wavelength selection algorithms and two classification algorithms were used to build decay detection models in pixel-level, as well as the two-band ratio images, pseudo-color image enhancement and improved watershed segmentation were used to build decay detection models in image-level. The imagelevel detection method proposed in this study obtained a total success rate of 92% for all fruit, indicating its potential to detect decayed oranges online. Moreover, the LW-NIR hyperspectral reflectance imaging is verified as a useful method to detect surface defects of fruits.
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