Camera Sensor Arrangement for Crop/Weed Detection Accuracy in Agronomic Images

被引:22
|
作者
Romeo, Juan [1 ]
Miguel Guerrero, Jose [1 ]
Montalvo, Martin [2 ]
Emmi, Luis [3 ]
Guijarro, Maria [1 ]
Gonzalez-de-Santos, Pablo [3 ]
Pajares, Gonzalo [1 ]
机构
[1] Univ Complutense, Fac Informat, Dept Software Engn & Artificial Intelligence, E-28040 Madrid, Spain
[2] Univ Complutense, Fac Informat, Dept Comp Architecture & Automat Control, E-28040 Madrid, Spain
[3] UPM, CSIC, Ctr Automat & Robot, Madrid, Spain
来源
SENSORS | 2013年 / 13卷 / 04期
关键词
weeds detection accuracy; crop lines detection accuracy; camera-based sensor; extrinsic and intrinsic parameters; uncontrolled illumination; lens vignetting correction; ROW CROPS; WEED; IDENTIFICATION; SEGMENTATION; SYSTEM;
D O I
10.3390/s130404348
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes. Accuracy of identification and detection is an important issue to be addressed in image processing. There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others. Moreover, in agricultural applications, the uncontrolled illumination, existing in outdoor environments, is also an important factor affecting the image accuracy. This paper is exclusively focused on two main issues, always with the goal to achieve the highest image accuracy in Precision Agriculture applications, making the following two main contributions: (a) camera sensor arrangement, to adjust extrinsic parameters and (b) design of strategies for controlling the adverse illumination effects.
引用
收藏
页码:4348 / 4366
页数:19
相关论文
共 50 条
  • [1] Modelling agronomic images for weed detection and comparison of crop/weed discrimination algorithm performance
    G. Jones
    Ch. Gée
    F. Truchetet
    Precision Agriculture, 2009, 10 : 1 - 15
  • [2] Modelling agronomic images for weed detection and comparison of crop/weed discrimination algorithm performance
    Jones, G.
    Gee, Ch.
    Truchetet, F.
    PRECISION AGRICULTURE, 2009, 10 (01) : 1 - 15
  • [3] Simulation of agronomic images for an automatic evaluation of crop/weed discrimination algorithm accuracy
    Jones, G.
    Gee, Ch.
    Truchetet, F.
    EIGHT INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION, 2007, 6356
  • [4] Crop/weed discrimination in perspective agronomic images
    Gee, Ch.
    Bossu, J.
    Jones, G.
    Truchetet, F.
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2008, 60 (01) : 49 - 59
  • [5] Wavelet transform to discriminate between crop and weed in agronomic images
    Bossu, Jeremie
    Gee, Christelle
    Truchetet, Frederic
    WAVELET APPLICATIONS IN INDUSTRIAL PROCESSING V, 2007, 6763
  • [6] Wavelet transform to discriminate between crop and weed in perspective agronomic images
    Bossu, J.
    Gee, Ch.
    Jones, G.
    Truchetet, F.
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2009, 65 (01) : 133 - 143
  • [7] Crop/weed discrimination in simulated images
    Jones, G.
    Gee, C.
    Truchetet, F.
    IMAGE PROCESSING: ALGORITHMS AND SYSTEMS V, 2007, 6497
  • [8] Development of methods based on double Hough Transform or Gabor filtering to discriminate between crop and weed in agronomic images
    Bossu, J
    Gée, C
    Guillemin, JP
    Truchetet, F
    MACHINE VISION APPLICATIONS IN INDUSTRIAL INSPECTION XIV, 2006, 6070
  • [9] Weed suppression and crop productivity by different arrangement patterns of maize
    Simic, M.
    Dolijanovic, Z.
    Maletic, R.
    Stefanovic, L.
    Filipovic, M.
    PLANT SOIL AND ENVIRONMENT, 2012, 58 (03) : 148 - 153
  • [10] The agronomic value of annual plant diversity in crop-weed systems
    Szumigalski, Anthony R.
    Van Acker, Rene C.
    CANADIAN JOURNAL OF PLANT SCIENCE, 2006, 86 (03) : 865 - 874