[1] 王志强.NIRSA快速分析茶叶品质方法的研究[D].镇江:江苏大学,2009.
[2] 赵杰文,陈全胜,张海东,等.近红外光谱分析技术在茶叶鉴别中的应用研究[J].光谱学与光谱分析,2006,26(9):1601-1604.
[3] 杨福增,杨亮亮,田艳娜,等.基于颜色和形状特征的茶叶嫩芽识别方法[J].农业机械学报,2009,40.
[4] Yu Huichun, Wang Jun, Yao Cong, et al. Quality grade identification of green tea using E-nose by CA and ANN[J]. Lebensmittel-Wissenschaft and-Technologie, 2008, 41(7):1268-1273.
[5] Borah S, Bhuyan M, Borah S. Quality indexing by machine vision during fermentation in black tea manufacturing[R]. Sixth International Conference on Quality Control by Artificial Vision,2003:468-475.
[6] 徐海卫,胡常安,汤江文,等.基于机器视觉的神经网络在茶叶鉴别中的应用[J].中国测试技术,2014(3):89-92.
[7] 叶能胜,谷学新,张立芹,等.指纹图谱技术与茶叶分类鉴别研究[C].中国化学会学术年会,2010.
[8] 邵明.基于计算机视觉的龙井茶叶嫩芽识别方法研究[D].杭州:中国计量学院,2013.
[9] 陈大力.数字图像处理中去噪算法的研究[D].沈阳:东北大学,2008.
[10] 王吉林,赵力.数字图像形状特征提取的研究[J].微电子学与计算机,2010,27(5):118-120.
[11] 赵高长,张磊,武风波.改进的中值滤波算法在图像去噪中的应用[J].应用光学,2011,32(4):678-682.
[12] Bednar J B. Applications of median filtering to deconvolution, pulse estimation, and statistical editing of seismic data[J]. Geophysics,2012,48(12):1598-1610.
[13] 黄志开.彩色图像特征提取与植物分类研究[D].合肥:中国科学技术大学,2006.
[14] Chen W T, Liu W C, Chen M S. Adaptive color feature extraction based on image color distributions.[J]. IEEE Trans Image Process,2010,19(8):2005-2016.
[15] Fazli S, Pour H M, Bouzari H. Particle Filter Based Object Tracking with Sift and Color Feature[C]// 2009 Second International Conference on Machine Vision. IEEE Computer Society,2009:89-93.
[16] 杨涛,张森林.一种基于HSV颜色空间和SIFT特征的车牌提取算法[J].计算机应用研究,2011,28(10):3937-3939.
[17] 黄国祥.RGB颜色空间及其应用研究[D].长沙:中南大学,2002.
[18] 郑成勇.一种RGB颜色空间中的车牌定位新方法[J].中国图象图形学报,2010,15(11):1623-1628.
[19] Sural S, Qian G, Pramanik S. Segmentation and histogram generation using the HSV color space for image retrieval[C]// Image Processing. 2002. Proceedings. 2002 International Conference on. IEEE,2002:589-592.
[20] 侯铜,姚立红,阚江明.基于叶片外形特征的植物识别研究[J].湖南农业科学,2009(4):123-125.
[21] Chen Y, Zhou P. Research on Shape and Texture Feature Extraction of Plant Leaf Images[J]. Journal of Zhejiang Sci-Tech University,2013.
[22] 吴冰,秦志远.自动确定图像二值化最佳阈值的新方法[J].测绘学院学报,2001,18(4):283-286.
[23] 郎宇宁,蔺娟如.基于支持向量机的多分类方法研究[J].中国西部科技,2010,9(17):28-29.
[24] 丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报:自然科学版,2011,40(1):2-10.
[25] Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, et al. Pegasos: primal estimated sub-gradient solver for SVM [J]. Mathematical Programming,2011,127(1):3-30.
[26] KB D, JC R, H W, et al. Multiple SVM-RFE for gene selection in cancer classification with expression data[C]. IEEE Trans Nanobioscience,2005:228-234.
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