| 基于形态学的香梨褐变核磁共振成像无损检测 |
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| 引用本文： | 周水琴,应义斌,商德胜.基于形态学的香梨褐变核磁共振成像无损检测[J].浙江大学学报(自然科学版 ),2012,46(12):2141-2145. |
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| 作者姓名： | 周水琴 应义斌 商德胜 |
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| 作者单位： | 1. 浙江大学 生物系统工程与食品科学学院,浙江 杭州 310058；2.杭州职业技术学院 友嘉机电学院,
浙江 杭州 310058；3.农业部设施农业装备与信息化重点实验室,浙江 杭州 310058；
4.浙江大学 医学院附属第一医院,浙江 杭州 310003 |
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| 基金项目： | 国家自然科学基金资助项目(30825027);2011杭州职业技术学院院级课题资助项目(ky201114) |
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| 摘 要： | 以新疆库尔勒香梨为研究对象,提出使用核磁共振成像技术检测香梨内部褐变的方法.采用核磁共振成像设备扫描得到香梨中部冠状面图像,使用MATLAB软件完成图像分割和中值滤波,采用自动阈值分割目标区域,利用图像面积区域属性函数分离果核与褐变部分,以提取香梨褐变特征,并对误判褐变切片图像作了进一步分析与处理.实验结果表明:核磁共振成像技术对不同贮藏周期的正常与褐变香梨切片图像的识别准确率分别为84%和100%,该方法对贮藏后期（6个月）香梨的褐变识别更有效.
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| 关 键 词： | 核磁共振成像 香梨 褐变 形态学 特征提取 |
Morphology based noninvasive detection for fragrant pears browning with magnetic resonance imaging |
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| ZHOU Shui-qin,YING Yi-bin,SHANG De-sheng.Morphology based noninvasive detection for fragrant pears browning with magnetic resonance imaging[J].Journal of Zhejiang University(Engineering Science),2012,46(12):2141-2145. |
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| Authors: | ZHOU Shui-qin YING Yi-bin SHANG De-sheng |
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| Affiliation: | 1.College of Biosystem Engineering and Food Science,Zhejiang University,Hangzhou 310058,China; 2.Fair Friend Institute of Electromechanics,Hangzhou Vocational and Technical College,Hangzhou 310058,China; 3.Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture,Ministry of Agriculture, Hangzhou 310058,China;4.The First Affiliated Hospital of Medical School of Zhejiang University, Hangzhou 310003,China) |
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| Abstract: | By adopting Korla fragrant pears (Pyrus bretehezderi Rehd.) as the experimental object, the nuclear magnetic resonance imaging (MRI) technology was proposed to detect the internal browning on fragrant pears. Coronal magnetic resonance images were acquired by horizontal scanning mode in the middle of pear. Image segmentation and median filter were finished by MATLAB software. Otsu’s threshold was used to segment object image. The feature of browning was extracted through the area property of image region which can distinguish browning with the kernel of pear. The misclassified browning slice images were further analyzed and reprocessing. The experimental results showed that detecting browning on pears with MRI was realized and the accuracy was 84% and 100% for sound and internal browning pears at different storage time respectively. The method for fragrant pear browning recognition with longer storage time(6 months) was more effective. |
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