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

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

doi:10.3390/foods13233843

Foods (Nov 2024)

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

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

Affiliations

Jian Wu: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China
Chenlin Liu: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China
Aiguo Ouyang: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China
Bin Li: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China
Nan Chen: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China
Jing Wang: Institute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agriculture Sciences, Beijing 100081, China
Yande Liu: Intelligent Mechanical and Electrical Equipment Innovation Research Institute, East China Jiaotong University, Nanchang 330013, China

DOI: https://doi.org/10.3390/foods13233843
Journal volume & issue: Vol. 13, no. 23
p. 3843

Abstract

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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.

Published in Foods

ISSN: 2304-8158 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/foods

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