利用高光谱成像和机器学习技术对不同小麦粉类型进行分类

IF 3.1 3区 物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION
Mohammad Hossein Nargesi , Kamran Kheiralipour , Digvir S. Jayas
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引用次数: 0

摘要

不同类型的小麦粉用于生产各种烘焙产品。由于这四种面粉的白度不同,可以使用高光谱成像技术来接收红外线波长。该技术使用线扫描系统,在 400-950 纳米范围内区分糖果面粉和 Samoun、Sangak 和 Tafton 面包的面粉。选择有效波长并从相应的图像通道中提取不同的图像特征。所选波长分别为 601.33、620.34、696.41、730.31、821.26 和 841.11 纳米。在 MATLAB 软件中使用线性判别分析、支持向量机和人工神经网络方法对提取的特征进行分类。人工神经网络的分类准确率高于其他方法。高效特征的分类准确率(98.1%)高于所有提取特征的分类准确率(96.9%)。结果表明,高光谱成像与人工神经网络相结合,具有很强的区分不同小麦粉类型的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of different wheat flour types using hyperspectral imaging and machine learning techniques

Different wheat flour types are used to produce various baked products. Due to the whiteness of the four types, hyperspectral imaging can be used due to receiving infrared wavelength. The technique was applied to distinguish confectionery flour and the flours of Samoun, Sangak, and Tafton breads using a line scanning system in the range of 400–950 nm. Effective wavelengths were selected and different image features were extracted from the corresponding image channels. The selected wavelengths were 601.33, 620.34, 696.41, 730.31, 821.26, and 841.11 nm. The extracted features were used in classification step using linear discriminant analysis, support vector machine, and artificial neural network methods in MATLAB software. The classification accuracy of artificial neural network was higher than the other methods. The efficient features gave higher classification accuracy (98.1 %) than all extracted features (96.9 %). The results showed the high ability of hyperspectral imaging combined with artificial neural network to distinguish different wheat flour types.

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来源期刊
CiteScore
5.70
自引率
12.10%
发文量
400
审稿时长
67 days
期刊介绍: The Journal covers the entire field of infrared physics and technology: theory, experiment, application, devices and instrumentation. Infrared'' is defined as covering the near, mid and far infrared (terahertz) regions from 0.75um (750nm) to 1mm (300GHz.) Submissions in the 300GHz to 100GHz region may be accepted at the editors discretion if their content is relevant to shorter wavelengths. Submissions must be primarily concerned with and directly relevant to this spectral region. Its core topics can be summarized as the generation, propagation and detection, of infrared radiation; the associated optics, materials and devices; and its use in all fields of science, industry, engineering and medicine. Infrared techniques occur in many different fields, notably spectroscopy and interferometry; material characterization and processing; atmospheric physics, astronomy and space research. Scientific aspects include lasers, quantum optics, quantum electronics, image processing and semiconductor physics. Some important applications are medical diagnostics and treatment, industrial inspection and environmental monitoring.
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