Early Detection of Slight Bruises in Yellow Peaches (Amygdalus persica) Using Multispectral Structured-Illumination Reflectance Imaging and an Improved Ostu Method

文献类型： 外文期刊

第一作者： Wu, Jian

作者： Wu, Jian;Liu, Chenlin;Ouyang, Aiguo;Li, Bin;Chen, Nan;Liu, Yande;Wu, Jian;Liu, Chenlin;Ouyang, Aiguo;Li, Bin;Chen, Nan;Liu, Yande;Wang, Jing

作者机构：

关键词： early detection; slight bruises; yellow peaches; multispectral structured-illumination reflectance imaging; I-Ostu method

期刊名称：FOODS （ 影响因子：5.1； 五年影响因子：5.6 ）

ISSN：

年卷期： 2024 年 13 卷 23 期

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收录情况： SCI

摘要： Assessing the internal quality of fruits is crucial in food chemistry and quality control, and bruises on peaches can affect their edible value and storage life. However, the early detection of slight bruises in yellow peaches is a major challenge, as the symptoms of slight bruises are difficult to distinguish. Herein, this study aims to develop a more simple and efficient structured-illumination reflectance imaging system (SIRI) and algorithms for the early nondestructive detection of slight bruises in yellow peaches. Pattern images of samples were acquired at spatial frequencies of 0.05, 0.10, 0.15, and 0.20 cycle mm-1 and wavelengths of 700, 750, and 800 nm using a laboratory-built multispectral structured-illumination reflectance imaging system (M-SIRI), and the direct component (DC) and alternating component (AC) images were obtained by image demodulation. A spatial frequency of 0.10 cycle mm-1 and wavelength of 700 nm were determined to be optimal for acquiring pattern images based on the analysis of the pixel intensity curve of the AC image; then, the pattern images of all yellow peaches samples were obtained. The ratio image (RT) between the AC image and the DC image significantly enhances bruise features. An improved Otsu algorithm is proposed to improve the robustness and accuracy of the Otsu algorithm against dark spot noise in AC and RT images. As a comparison, the global thresholding method and the Otsu method were also applied to the segmentation of the bruised region in all samples. The results indicate that the I-Otsu algorithm has the best segmentation performance for RT images, with an overall detection accuracy of 96%. This study demonstrates that M-SIRI technology combined with the I-Otsu algorithms has considerable potential in non-destructive detection of early bruises in yellow peaches.

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