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图像处理技术在冬小麦叶面积指数测定中的应用 被引量:29

Application of Image Processing Technology in Wheat Canopy Leaf Area Index Measuring
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摘要 为了探讨利用图像处理技术测定冬小麦叶面积指数的可行性,在室外光照条件下,固定数码相机高度垂直拍摄冬小麦群体图像,利用图像处理技术获取小麦冠层的图像叶面积指数(ILAI),并用手工测量获得小麦群体实际叶面积指数(LAI),建立ILAI和LAI间与施肥处理有关的关系模型,对该模型的稳定性和实用性进行统计检验。试验结果表明,利用图像处理技术通过ILAI获取小麦LAI是可行的,且简便易行,测量精度和效率都很高。 A method of measuring winter wheat leaf area index based on image processing technology was (studied). In the outdoor ray, the test was to get wheat canopy image leaf area index (ILAI) with digital camera in fixed height, and obtain wheat leaf area index (LAI) by handing measure at the same time. The model was made between ILAI and LAI in the condition of different fertilizer levels, and its stabilization and practicality were tested . Generally, the results showed that this method had better feasibility, higher precision and higher efficiency.
出处 《麦类作物学报》 CAS CSCD 2004年第4期108-112,共5页 Journal of Triticeae Crops
基金 国家"十五"科技攻关种植业信息系统项目。
关键词 叶面积指数 冬小麦 LAI 施肥处理 利用 冠层 群体 效率 定数 获取 Leaf area index (LAI) Image processing Model
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参考文献15

  • 1庞红喜,宋哲民,闵东红.不同穗型小麦品种叶重与叶面积关系的研究[J].麦类作物,1998,18(1):39-40. 被引量:26
  • 2艾军 李爱民 等.北五味子不同株系间叶形指数无本质差异[J].特产研究,1999,1:43-44.
  • 3张思玉,杨辽,兰海涛,胥辉.阔叶树叶面积求算的新方法[J].新疆农业大学学报,1995,18(3):96-99. 被引量:3
  • 4袁哲明,傅凌才.用扫描仪测定害虫食叶面积[J].湖南农业大学学报(自然科学版),1997,23(5):472-473. 被引量:15
  • 5朱志刚译.数字图像处理[M].北京:电子工业出版社,1998..
  • 6张恒敢,杨四军,顾克军,李德民.应用数字图像处理测定作物叶面积的简便方法[J].江苏农业科学,2002,30(3):20-21. 被引量:49
  • 7Yonekawa S, Sakai N, Kitani O. Identification of idealized leaf types using simple dimensionless shape factors by image analysis[J]. Trans of the ASAE, 1996, 39(4):1525-1533.
  • 8Granitto P M, Navone H D, Verdes P F, et al. Computers and electronics in agriculture[J]. Trans of the ASAE, 2002, 33(2):91-103.
  • 9Woebbecke D M, G E Meyer, K Von-Bargen, et al. Shape features for identifying young weeds using image analysis[J]. Trans of the ASAE, 1995, 38(1):271-281.
  • 10Sarkar N, Wolfe R R. Image processing for tomato grading[J]. Trans of the ASAE, 1990, 33(4):564-572.

二级参考文献45

  • 1Gunasekaran S, Cooper T M, Berlage A G, et al. Image Processing for Stress cracks in Corn Kernels. [J] Trans of the ASAE, 1988,31:257--263.
  • 2Berlage A G, Cooper T M, Aristazabal J F. Machine Vision Identification of Diploid and Tetraploid Ryegrass Seed[J]. Transof the ASAE, 1988,31(1) :24--27.
  • 3Rigney M P, Kranzler G A. Machine Vision for Grading Southern pine seedlings[J]. Trans of the ASAE, 1988,31 (2) : 642--646.
  • 4Delwiche M J, Tang S, Thompson J f. Prune Defect Detection by Line-scan Imaging[J]. Trans of the ASAE, 1990,33(3):950--954.
  • 5Elster R T, Goodrum J W. Detection of Cracks in Eggs Using machine vision[J]. Trans of the ASAE, 1991,34(1) :307--312.
  • 6Kranzler G A. Applying Digital Image Processing in Agriculture[J]. Agricultural Engineering, 1985, 66(3):11--14.
  • 7Liao K, Paulsen M R, Reid J F, et al, Corn Kernel Breakage Classification by Machine Vision Using a Neural Network Classifier[J], Trans of the ASAE, 1993,36(6) :1949-- 1953.
  • 8Rigney M P, Brusewitz G H, Kranzler G A. Asparagus Defect inspection with machine vision[J]. Trans of the ASAE, 1992,35(6):1873--1878.
  • 9Sarkar N, Wolfe R R. Image Prossing for Tomato Grading[J].Trans of the ASAE, 1990,33(4):564--572.
  • 10Shearer S A, Payne F A. Color and Defect Sorting of Bell Peppers Using Machine Vision[J]. Trans of the ASAE, 1990,33(6):2045--2050.

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