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毕业论文网 > 任务书 > 机械机电类 > 机械设计制造及其自动化 > 正文

基于光谱成像的指标像素分布检测仿真研究任务书

 2022-01-25 11:01  

全文总字数:8171字

1. 毕业设计(论文)的内容、要求、设计方案、规划等

前言中包括对基于光谱成像开展指标空间分布检测的研究进展的描述,指出开展基于区域光谱建立化学计量学模型进行像素光谱指标检测、以及对检测结果开展数值验证研究的必要性。

方案:采用模拟仿真方法,人工生成检测区域内各空间位置处的像素光谱,提取合成区域均值光谱进行化学计量学建模、进行像素位置指标验证。

对比不同区域光谱生成方式对像素位置光谱的检测精度影响、及有无噪声情况对像素光谱的检测精度影响。

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2. 参考文献(不低于12篇)

[ ] 肖松山, 范世福, 李昀,等. 光谱成像技术进展[J]. 现代仪器, 2004, 5(5):5-8.[ ] 杨康. 空间目标高光谱特性分析[D]. 上海交通大学, 2011.[ ] 张若岚, 陈洁. 从单波段到超光谱面向多维信息感知的红外光谱成像技术[J]. 红外技术, 2014, 4(4):257-264.[ ] Elmasry, G., Sun, D.-W., Allen, P. Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef[J]. Journal of Food Engineering, 2012, 110(1):127140.[ ] Elmasry, G., Iqbal, A., Sun, D.-W., et al. Quality classification of cooked, sliced turkey hams using NIR hyperspectral imaging system[J]. Journal of Food Engineering, 2011, 103(3):333344.[ ] Kamruzzaman, M., Elmasry, G., Sun, D.-W., et al. Application of NIR hyperspectral imaging for discrimination of lamb muscles[J]. Journal of Food Engineering, 2011, 104(3):332-340.[ ] Kamruzzaman, M., Elmasry, G., Sun, D.-W., et al.Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression[J]. Innovative Food Science Emerging Technologies, 2012, 16(39):218226.[ ] Wang, X., Zhao, M., Ju, R., et al. Visualizing quantitatively the freshness of intact fresh pork using acousto-optical tunable filter-based visible/near-infrared spectral imagery[J]. Computers Electronics in Agriculture, 2013, 99(7):4153.[ ] 汪希伟. 基于光谱成像的猪肉新鲜度检测方法[D]. 南京林业大学, 2014.[ ] ElMasry, G., Sun, D.-W., Allen, P. Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging[J]. Food Research International, 2011, 44(9): 2624-2633.[ ] Kamruzzaman, M., ElMasry, G., Sun, D.-W., et al. Prediction of some quality attributes of lamb meat using near-infrared hyperspectral imaging and multivariate analysis[J]. Analytica chimica acta, 2012, 714: 57-67.[ ] Kamruzzaman, M., Makino, Y., Oshita, S. Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging[J]. Food Chemistry, 2015.[ ] Xiong, Z., Sun, D.-W., Xie, A. Potential of hyperspectral imaging for rapid prediction of hydroxyproline content in chicken meat, et al. .[J]. Food Chemistry, 2015, 175:417-422.[ ] Xiong, Z., Sun, D.-W., Xie, A., et al. Quantitative determination of total pigments in red meats using hyperspectral imaging and multivariate analysis[J]. Food chemistry, 2015, 178: 339-345.[ ] Garrido-Novell, C., Garrido-Varo, A., Prez-Marn, D., et al. Quantification and spatial characterization of moisture and NaCl content of Iberian dry-cured ham slices using NIR hyperspectral imaging[J]. Journal of Food Engineering, 2015, 153(153):117123.[ ] Pu, H., Sun, D.-W., Ma, J., et al. Hierarchical variable selection for predicting chemical constituents in lamb meats using hyperspectral imaging[J]. Journal of Food Engineering, 2014, 143(2):4452.[ ] Liu, D., Qu, J., Sun, D.-W., et al. Non-destructive prediction of salt contents and water activity of porcine meat slices by hyperspectral imaging in a salting process[J]. Innovative Food Science Emerging Technologies, 2013, 20: 316-323.[ ] Liu, D., Sun, D.-W., Qu, J., et al. Feasibility of using hyperspectral imaging to predict moisture content of porcine meat during salting process[J]. Food chemistry, 2014, 152: 197-204.[ ] Feng, Y.-Z., Sun, D.-W. Determination of total viable count (TVC) in chicken breast fillets by near-infrared hyperspectral imaging and spectroscopic transforms[J]. Talanta, 2013, 105(4):244249.[ ] Barbin, D. F., ElMasry, G., Sun, D.-W., et al. Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging[J]. Food chemistry, 2013, 138(2): 1162-1171.[ ] Cheng, J.-H., Sun, D.-W., Pu, H.-B., et al. Suitability of hyperspectral imaging for rapid evaluation of thiobarbituric acid (TBA) value in grass carp (Ctenopharyngodon idella) fillet[J]. Food chemistry, 2015, 171: 258-265.[ ] Cheng, J.-H., Sun, D.-W., Pu, H., et al. Development of hyperspectral imaging coupled with chemometric analysis to monitor K value for evaluation of chemical spoilage in fish fillets[J]. Food Chemistry, 2015, 185:245253.[ ] Cheng, J.-H., Sun, D.-W. Rapid and non-invasive detection of fish microbial spoilage by visible and near infrared hyperspectral imaging and multivariate analysis[J]. LWT-Food Science and Technology, 2015, 62(2): 1060-1068.[ ]Dai, Q., Cheng, J.-H., Sun, D.-W., et al. Potential of hyperspectral imaging for non-invasive determination of mechanical properties of prawn (Metapenaeus ensis)[J]. Journal of Food Engineering, 2014, 136(6):6472.[ ] Dai, Q., Cheng, J.-H., Sun, D.-W., et al. Prediction of Total Volatile Basic Nitrogen Contents using Wavelet Features from Visible/Near-infrared Hyperspectral Images of Prawn (Metapenaeus ensis)[J]. Food Chemistry, 2015.[ ] Xu, J.-L., Riccioli, C., Sun, D.-W. Efficient Integration of Particle Analysis in Hyperspectral Imaging for Rapid Assessment of Oxidative Degradation in Salmon Fillet[J]. Journal of Food Engineering, 2015, 169.[ ] He, H.-J., Wu, D., Sun, D.-W. Non-destructive and rapid analysis of moisture distribution in farmed Atlantic salmon (Salmo salar) fillets using visible and near-infrared hyperspectral imaging[J]. Innovative Food Science Emerging Technologies, 2013, 18: 237-245.[ ] He, H.-J., Wu, D., Sun, D.-W. Rapid and non-destructive determination of drip loss and pH distribution in farmed Atlantic salmon (Salmo salar) fillets using visible and near-infrared (VisNIR) hyperspectral imaging[J]. Food chemistry, 2014, 156: 394-401.[ ] He, H.-J., Sun, D.-W., Wu, D. Rapid and real-time prediction of lactic acid bacteria (LAB) in farmed salmon flesh using near-infrared (NIR) hyperspectral imaging combined with chemometric analysis[J]. Food Research International, 2014, 62: 476-483.[ ] He, H.-J., Wu, D., Sun, D.-W. Potential of hyperspectral imaging combined with chemometric analysis for assessing and visualising tenderness distribution in raw farmed salmon fillets[J]. Journal of food engineering, 2014, 126: 156-164.[ ] Wu, D., Sun, D.-W., He, Y. Novel non-invasive distribution measurement of texture profile analysis (TPA) in salmon fillet by using visible and near infrared hyperspectral imaging[J]. Food chemistry, 2014, 145: 417-426.[ ] Wu, D., Sun, D.-W. Application of visible and near infrared hyperspectral imaging for non-invasively measuring distribution of water-holding capacity in salmon flesh[J]. Talanta, 2013, 116: 266-276.[ ] Wu, D., Sun, D.-W. Potential of time series-hyperspectral imaging (TS-HSI) for non-invasive determination of microbial spoilage of salmon flesh[J]. Talanta, 2013, 111: 39-46.[ ] Yang, Y.-C., Sun, D.-W., Pu, H., et al. Rapid detection of anthocyanin content in lychee pericarp during storage using hyperspectral imaging coupled with model fusion[J]. Postharvest Biology and Technology, 2015, 103: 55-65.[ ] Lee, W.-H., Kim, M. S., Lee, H., et al. Hyperspectral near-infrared imaging for the detection of physical damages of pear[J]. Journal of Food Engineering, 2014, 130: 1-7.[ ] Pu, Y.-Y., Sun, D.-W. Prediction of moisture content uniformity of microwave-vacuum dried mangoes as affected by different shapes using NIR hyperspectral imaging[J]. Innovative Food Science Emerging Technologies, 2015.[ ] Jiang, J., X, Qiao., R, He., Use of Near-Infrared hyperspectral images to identify moldy peanuts[J]. Journal of Food Engineering, 2016, 169: 284-290.[ ] Kandpal, L. M., Lee, S., Kim, M. S., et al. Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B1 (AFB1) on corn kernels[J]. Food Control, 2015, 51:171-176.[ ] Zou, X., Zhao, J., Holmes, M., et al. Independent component analysis in information extraction from visible/near-infrared hyperspectral imaging data of cucumber leaves[J]. Chemometrics Intelligent Laboratory Systems, 2010, 104(2):265-270.

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