人工智能
计算机视觉
图像处理
计算机科学
集合(抽象数据类型)
模式识别(心理学)
图像质量
热成像
图像(数学)
光学
物理
红外线的
程序设计语言
作者
Giaime Ginesu,Daniele Giusto,Volker Märgner,Peter Meinlschmidt
出处
期刊:IEEE Transactions on Industrial Electronics
[Institute of Electrical and Electronics Engineers]
日期:2004-04-01
卷期号:51 (2): 480-490
被引量:111
标识
DOI:10.1109/tie.2004.825286
摘要
This paper deals with the problem of detection of foreign bodies in food. A new method for inspecting food samples is presented, using thermographic images to detect foreign bodies that are not detectable using conventional methods. At first, the basic background of thermography is given. Then, experiments to obtain well-contrasted thermographic images of different food and foreign bodies are discussed. The main part of the present paper introduces specific image processing methods that show a good recognition power of foreign bodies within food. Results achieved with a small set of test images are presented. The results are promising and the methods work even on some poorly contrasted images. To compare the different image processing and recognition methods, a quality index is defined. On the test images the success of the presented methods is shown and the difference in recognition results can be measured using the introduced quality index.
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