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Detection of early decay in navel oranges by structured-illumination reflectance imaging combined with image enhancement and segmentation

文献类型： 外文期刊

作者： Li, Jiangbo 1 ; Lu, Yuzhen 2 ; Lu, Renfu 4 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing, Peoples R China

2.Mississippi State Univ, Dept Agr & Biol Engn, Mississippi State, MS 39762 USA

3.Michigan State Univ, Dept Biosyst & Agr Engn, E Lansing, MI 48824 USA

4.Agr Res Serv, US Dept Agr, E Lansing, MI 48824 USA

关键词： Citrus; Early decay detection; Structured illumination; Image enhancement; Defect segmentation

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： 2023 年 196 卷

页码：

收录情况： SCI

摘要： Early detection and removal of decayed fruit is critical for reducing product and economic losses for the fruit industry. It is, however, challenging to detect tissue decay in the early stage, which has no or few visual symptoms. This study was intended to evaluate the feasibility of an emerging structured-illumination reflectance imaging (SIRI) technique for early detection of decay in navel oranges. Pattern images were acquired from navel oranges five days after the fruit had been inoculated with fungal spores of Penicillium digitatum (P. digitatum) (the most important pathogen responsible for citrus decay), using an inhouse assembled multispectral imaging platform under phase-shifted sinusoidal illumination at four spatial frequencies (0.05, 0.10, 0.15 and 0.20 cycles mm(-1)) and three wavelengths (690, 730 and 810 nm). The pattern images were processed through demodulation to obtain direct component (DC) and amplitude component (AC) images for each wavelength and spatial frequency. The AC images were able to reveal decayed areas in the fruit. The wavelength of 810 nm and a spatial frequency of 0.20 cycles mm(-1) were determined to be optimal for decayed tissue detection, based on quantitative assessment of the contrast between decayed and sound tissues in images. Moreover, the ratio image (R-DC/AC) between the AC and DC images and the corrected ratio image (Rc), which was obtained by applying the image brightness transform to R-DC/AC, have showed improved defect contrast and background uniformity. Three image segmentation methods including watershed, Otsu and global thresholding were applied for segmenting decayed areas in the AC, R-DC/AC and R-C images. The R-C images produced the best detection performance with an overall detection accuracy of over 97 %. This study has demonstrated that when combined with appropriate image processing methods, the SIRI technique is effective for the early detection of decay in citrus fruit.

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