| 基于计算机视觉的鸡蛋新鲜度无损检测 |
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| 引用本文： | 郑丽敏,杨 旭,徐桂云,郭慧媛,任发政,吴 平,朱 虹,葛克山.基于计算机视觉的鸡蛋新鲜度无损检测[J].农业工程学报,2009,25(13):335-339. |
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| 作者姓名： | 郑丽敏 杨 旭 徐桂云 郭慧媛 任发政 吴 平 朱 虹 葛克山 |
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| 作者单位： | 中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学动物科技学院，北京 100094;中国农业大学食品科学与营养工程学院，北京 100083;中国农业大学食品科学与营养工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学食品科学与营养工程学院，北京 100083 |
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| 基金项目： | 国家“十一五”支撑计划项目（2006BAD14B04，2006BAD22B06）和现代农业产业技术体系建设专项资金资助 |
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| 摘 要： | 对鸡蛋的新鲜度、贮藏期进行无损检测，在鸡蛋生产、流通、加工领域具有重要意义。该文进行了鸡蛋新鲜度（哈夫值）常规指标在一定温度条件下随贮藏时间变化的试验，采用高分辨率的工业化数字摄像头，以冷光源背向照明方式（照度为10 000 Lx）获取数字图像，并提取了鸡蛋的图像特征蛋黄指数和气室指数。建立了鸡蛋新鲜度与蛋黄指数、贮藏时间与鸡蛋新鲜度、贮藏时间与蛋黄指数和气室指数的关系模型。得知鸡蛋新鲜度与蛋黄指数呈线性相关性，经检验实测值与预测值平均相对误差为6%；贮藏时间与鸡蛋新鲜度以及贮藏时间与鸡蛋蛋黄指数、鸡蛋气室指数均具有二次函数关系，经检验实测值与预测值绝对误差不超过2 d。结果表明基于计算机视觉技术、采用背向照明方式采集的鸡蛋的透射图像得到鸡蛋的蛋黄和气室的图像信息，可以预测鸡蛋的新鲜度和贮藏期。
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| 关 键 词： | 机器视觉，图像处理，无损检测，新鲜度，贮藏期，鸡蛋 |
| 收稿时间： | 2009/6/30 0:00:00 |
| 修稿时间： | 2009/9/11 0:00:00 |
Non destructive detection of egg freshness based on computer vision |
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| Zheng Limin,Yang Xu,Xu Guiyun,Guo Huiyuan,Ren Fazheng,Wu Ping,Zhu Hong and Ge Keshan.Non destructive detection of egg freshness based on computer vision[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(13):335-339. |
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| Authors: | Zheng Limin Yang Xu Xu Guiyun Guo Huiyuan Ren Fazheng Wu Ping Zhu Hong and Ge Keshan |
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| Institution: | 1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,3. College of Animal Science and Technology, China Agricultural University, Beijing 100083, China,2. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China,2. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China,1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China and 2. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China |
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| Abstract: | Non-destructive detection of egg freshness and storage time has great significance in the fields of egg production, transportation and processing. The experiment of egg freshness (Haff value) changes with storage time under the certain temperature was carried out. Digital images were achieved by high-resolution digital cameras with cold light illumination in reverse direction (intensity of illumination is approximate 10 000 Lx), and the index of egg yolk and the index of egg air room from image characters were extracted. The relational models of egg freshness with index of egg yolk, storage time with egg freshness, storage time with index of egg yolk and index of egg air room were established. Egg freshness with index of egg yolk showed linear relationship and the average relative error between actual test data and predicted data was 6% after detection. Storage time with egg freshness and storage time with index of egg yolk and index of egg air room showed quadratic function relationship and the average relative error was less than two days. Experimental results show that image information of egg yolk and air room from egg transillumination images generated with reverse direction lighting method on the computer vision can predict egg freshness and storage time. |
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| Keywords: | computer vision image processing non-destructive detection freshness storage time egg |
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