Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine | |
Wu, Di ; Yang, Haiqing ; Chen, Xiaojing ; He, Yong ; Li, Xiaoli ; Chen XJ(陈孝敬) | |
刊名 | http://dx.doi.org/10.1016/j.jfoodeng.2008.03.005
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2008-10 | |
关键词 | GREEN TEA OOLONG TEAS CLASSIFICATION BLACK IDENTIFICATION SPECTROSCOPY POLYPHENOLS COMPONENTS CATECHINS CAFFEINE |
英文摘要 | Multi-spectral imaging technique was applied to sorting the green tea category. 320 images were captured at three wavelengths (580, 680 and 800 nm) using a multi-spectral digital camera. Entropy values of images were obtained as image texture features. The correction answer rate of least squares-support vector machine (LS-SVM) with radial basis function kernel was up to 100% which was better than those of LS-SVM with linear kernel, partial least squares and radial basis function neural networks, respectively. Results of generation ability test shows that LS-SVM with radial basis function kernel could be effectively used for the application on a few samples. It could be concluded that it is possible to take multi-spectral images of tea and tell which category it is. The whole process is simple, fast, non-destructive and easy to operate. (c) 2008 Elsevier Ltd. All rights reserved. |
语种 | 英语 |
出版者 | J FOOD ENG |
内容类型 | 期刊论文 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/91743] ![]() |
专题 | 物理技术-已发表论文 |
推荐引用方式 GB/T 7714 | Wu, Di,Yang, Haiqing,Chen, Xiaojing,et al. Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine[J]. http://dx.doi.org/10.1016/j.jfoodeng.2008.03.005,2008. |
APA | Wu, Di,Yang, Haiqing,Chen, Xiaojing,He, Yong,Li, Xiaoli,&陈孝敬.(2008).Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine.http://dx.doi.org/10.1016/j.jfoodeng.2008.03.005. |
MLA | Wu, Di,et al."Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine".http://dx.doi.org/10.1016/j.jfoodeng.2008.03.005 (2008). |
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