Identification of early decayed oranges using structured-illumination reflectance imaging coupled with fast demodulation and improved image processing algorithms
文献类型： 外文期刊
作者： Li, Jiangbo 1 ; Lu, Yuzhen 2 ; Lu, Renfu 3 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing, Peoples R China
2.Michigan State Univ, Dept Biosyst & Agr Engn, E Lansing, MI 48824 USA
3.United States Dept Agr Agr Res Serv, E Lansing, MI 48824 USA
关键词： Citrus decay; Defect segmentation; Brightness transformation; Image enhancement; Classification
期刊名称：POSTHARVEST BIOLOGY AND TECHNOLOGY （ 影响因子：7.0； 五年影响因子：6.9 ）
ISSN： 0925-5214
年卷期： 2024 年 207 卷
页码：
收录情况： SCI
摘要： Effective detection of decayed oranges (Citrus genus) at the early stage is challenging because there are no or few visual symptoms on the infected fruit. Structured-illumination reflectance imaging (SIRI) has been proven effective for enhanced detection of subsurface defects in fruit. Amplitude component (AC) images retrieved from the original SIRI patterned images are useful for defect detection, but generally require acquiring three phase shifted pattern images, which limits the imaging and detection speed. Moreover, the AC images may also suffer from noticeable uneven brightness due to fruit curvature, which affects the identification of decayed areas. This study was therefore aimed to explore faster image demodulation, enhancement and processing algorithms, based on a specially developed SIRI technology, for effective identification of early decayed oranges. Pattern images were acquired, using three phase-shifted sinusoidal illumination patterns at the wavelength of 810 nm and a spatial frequency of 0.20 cycles mm-1, from the orange samples infected with Penicillium digitatum fungus, the most serious and devastating pathogen for orange fruit. Two-dimensional spiral phase transform was used to obtain AC images from one or two pattern images. The acquired AC images were then processed by using simple brightness adjustment and integral image-based fast average filtering for brightness correction, and improved watershed algorithm and global threshold for segmentation of decayed areas. Three different combinations of these image processing procedures for single and two pattern images were proposed to distinguish decayed oranges from sound ones. The three methodologies all achieved high overall identification rates of 97.5%, 95.0% and 95.3%, when the stem-end effect was also considered. This study showed that accurate detection of early decayed orange fruit can be achieved by using one or two phase-shifted pattern images, which would be beneficial for real-time implementation of the technique.
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