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光谱导航技术在果树果实定位中的应用 被引量:1

Spectral Navigation Technology and Its Application in Positioning the Fruits of Fruit Trees
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摘要 将光谱技术与导航技术有机结合是光谱分析技术的一个新颖且重要的应用方向。果实表面的反射光谱特征是果实物质的一种固有特征,果实与树叶、树枝的反射光谱在多个波段都有明显差异,根据果实表面反射光谱的不同,进行导航定位是一项具有实用意义的研究课题。文章提出了一种光谱导航技术,将果实、树叶、树枝的反射光谱作为一个重要的导航参数,利用其差异进行导航。研究结果表明,果树叶光谱在可见-红外区具有明显的"平坦效应";果树枝光谱则是在很宽的波长范围内具有平稳的上升趋势;而果实的反射率具有波动性变化。在850 nm处果实和叶子之间的反射率有较大差别,在这个波段附近设计阈值,则很容易识别果实与树叶。所提出的方法不仅可以快速区分果实、树叶和树枝,还可以有效消除外界环境的干扰。与传统的计算机视觉导航方法相比,光谱导航技术在果树果实定位方面具有一定的特色。 An innovative technology of spectral navigation is presented in the present paper. This new method adopts reflectance spectra of fruits, leaves and branches as one of the key navigation parameters and positions the fruits of fruit trees relying on the diversity of spectral characteristics. The research results show that the distinct smoothness as effect is available in the spectrum of leaves of fruit trees. On the other hand, gradual increasing as the trend is an important feature in the spectrum of branches of fruit trees while the spectrum of fruit fluctuates. In addition, the peak diversity of reflectance rate between fruits and leaves of fruit trees is reached at 850 nm of wavelength. So the limit value can be designed at this wavelength in order to distinguish fruits and leaves. The method introduced here can not only quickly distinguish fruits, leaves and branches, but also avoid the effects of surroundings. Compared with the traditional navigation systems based on machine vision, there are still some special and unique features in the field of positioning the fruits of fruit trees using spectral navigation technology.
出处 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2010年第3期770-773,共4页 Spectroscopy and Spectral Analysis
基金 国家自然科学基金项目(10722043) 航空科学基金项目(05G52047) 江苏省国际科技合作计划项目(BZ2008060) 国家留学基金项目(2008104769)资助
关键词 光谱导航 果实定位 反射光谱 导航参数 Spectral navigation Fruit positioning Reflectance spectrum Navigation parameters
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参考文献13

  • 1Leemans V,Magein H,Destain M F.Biosystems Engineering,2002,83(4):391.
  • 2Panigrahi S,Misra M K,Willson S.Computers and Electronics in Agriculture,1998,20(1):1.
  • 3Reed J N,Miles S J,Butler J,et al.Journal of Agricultural Engineering Research,2001,78(1):15.
  • 4应义斌.水果形状的傅里叶描述子研究[J].生物数学学报,2001,16(2):234-240. 被引量:22
  • 5黄星奕,魏海丽,赵杰文.实时在线检测苹果果形的一种计算方法[J].食品与机械,2006,22(1):27-29. 被引量:10
  • 6Sarig Y.Journal of Agricultural Engineering Research,1993,54:265.
  • 7Wang J,Maiorov M,Jeffries J B,et al.Measurement Science & Technology,2000,11:1578.
  • 8Dupuis G,Elias M,Simonot L.Applied Spectroscopy,2002,58(10):1329.
  • 9Petrich W,Staib A,Otto M,et al,Vibrational Spectroscopy,2002,28(1):117.
  • 10Bacci M,Casini A,Cueci C.Journal of Cultural Heritage,2003,4(4):329.

二级参考文献24

  • 1[1]Sarkar N, Wolfe R R. Computer vision based system for quality separation of fresh market tomatoes[J]. Transactions of the ASAE, 1985, 28(5):1714-1718.
  • 2[2]Sarkar N, Wolfe R R. Feature extraction techniques for sorting tomatoes by compuer vision[J]. Transactions of the ASAE, 1985, 28(3):970-974,979.
  • 3[3]Howarth M S, Brandon J R, Searcy S W, et al. Estimation of tip shape for carrot classification by machine vision[J]. Journal pf Agricultural Engineering Research, 1992, 53(1):123-139.
  • 4[4]Guyer D E, Miles G E, Schreiber M M,et al. Machine vision and image processing for plant identification[J]. Transactions of the ASAE, 1986, 29(6):1500-1507.
  • 5[5]Wolfe R R, Swaminathan M. Determining orientation and shape of bell peppers by machine vision[J]. Transactions of the ASAE, 1987, 30(6):1853-1856.
  • 6[6]Varghese Z C, Morrow T, Heinenann P H. Automated inspection of golden delicious apples using color computer vision[C]. 1991, ASAE paper, 91-7000.
  • 7[7]Van De Vooren J G, Polder G, Van Der Heijden W A M. Identification of mushrooms cultivars using image analysis[J]. Transactions of the ASAE, 1992, 35(1):347-350.
  • 8[8]Heinemann P H, Sommer H J Ⅲ, Morrow C T, et al. Machine vision based station for grading of "Golden Delicious” Apples[C]. 1995, Proceedings of the FAC Ⅳ Conference, 239-248.
  • 9V.Leemans,H.Magein,M.-F.Destain.On-line Fruit Grading according to their External Quality using Machine Vision [ J ].Biosystems Engineering,2002,83 (4):391 ~ 404.
  • 10Panigrahi S,Misra M K,Willson,S.Evaluations of fractal geometry and invariant moments for shape classification of corn germplasm[J].Computers and Electronics in Agriculture,1998,20 (1):1 ~ 20.

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