Image based leaf segmentation and counting in rosette plants

Information Processing in Agriculture - Tập 6 - Trang 233-246 - 2019
J. Praveen Kumar1, S. Domnic1
1National Institute of Technology, Tiruchirappalli, India

Tài liệu tham khảo

Minervini, 2016, Finely-grained annotated datasets for image-based plant phenotyping, Pattern Recogn Lett, 81, 80, 10.1016/j.patrec.2015.10.013 Lobet, 2013, An online database for plant image analysis software tools, Plant Methods, 9, 1, 10.1186/1746-4811-9-1 Scharr, 2016, Leaf segmentation in plant phenotyping: a collation study, Mach Vision Appl, 27, 585, 10.1007/s00138-015-0737-3 Huang, 2010, An automatic machine vision-guided grasping system for phalaenopsis tissue culture plantlets, Comput Electron Agric, 70, 42, 10.1016/j.compag.2009.08.011 Brochier, 2015, Tree leaves extraction in natural images: comparative study of preprocessing tools and segmentation methods, IEEE Trans Image Process, 24, 1549, 10.1109/TIP.2015.2400214 Tang X, Liu M, Zhao H, Tao W. Leaf extraction from complicated background. In: Proc CISP ’09 Proceedings of the 2009 International Congress on Image and Signal Processing. Tianjin, China; 2009. p. 1–5. Chene, 2012, On the use of depth camera for 3D phenotyping of entire plants, Comput Electron Agric, 82, 122, 10.1016/j.compag.2011.12.007 Yin X, Liu X, Chen J, Kramer DM. Multi-leaf tracking from fluorescence plant videos. In: Proc ICIP ’14 Proceedings of the 2014 IEEE international conference on image processing. Paris, France; 2014. p. 408–12. Dellen, 2015, Growth signatures of rosette plants from time-lapse video, IEEE/ACM Trans Comput Biol Bioinf, 12, 1470, 10.1109/TCBB.2015.2404810 DeVylder J, Ochoa D, Philips W, Chaerle L, VanDerStraeten D. Leaf segmentation and tracking using probabilistic parametric active contours. In: Proc. MIRAGE ’11 Proceedings of the 2011 International Conference on Computer Vision/Computer Graphics Collaboration Techniques. Rocquencourt, France; 2011. p. 75–85. Shen WZ, Zhang CL, Chen ZL. Research on automatic counting soybean leaf aphids system based on computer vision technology. In: Proc. ICMLC ‘07 Proceedings of the 2007 International Conference on Machine Learning and Cybernetics. Hong Kong, China; 2007. p. 1635–38. Cerutti G, Tougne L, Vacavant A, Coquin D. A parametric active polygon for leaf segmentation and shape estimation. In: Proc. ISVC ‘11 Proceedings of the 2011 International Symposium on Visual Computing. Las Vegas, USA; 2011. p. 202–13. DeVylder, 2012, Rosette tracker: an open source image analysis tool for automatic quantification of genotype effects, Plant Physiol., 160, 1149, 10.1104/pp.112.202762 Arbelaez, 2011, Contour detection and hierarchical image segmentation, IEEE Trans Pattern Anal Mach Intell, 33, 898, 10.1109/TPAMI.2010.161 Ning, 2010, Interactive image segmentation by maximal similarity based region merging, Pattern Recogn, 43, 445, 10.1016/j.patcog.2009.03.004 An, 2016, Plant high-throughput phenotyping using photogrammetry and imaging techniques to measure leaf length and rosette area, Comput Electron Agric, 127, 376, 10.1016/j.compag.2016.04.002 Toro, 2015, Superpixel-based roughness measure for multispectral satellite image segmentation, Remote Sens, 7, 14620, 10.3390/rs71114620 Wu, 2015, Superpixel-based image noise variance estimation with local statistical assessment, J Image Video, 38, 1 Ganesan P, Rajini V, Sathish BS, Khamar Basha Shaik. HSV colour space based segmentation of region of interest in satellite images. In: Proc. ICCICCT ’14 Proceedings of the 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies. Kanyakumari, India; 2014. p. 101–105. Ojo JA, Solomon ID, Adeniran SA. Contrast enhancement algorithm for colour images. In: Proc. SAI ‘15 Proceedings of the 2015 Science and Information Conference. London, UK; 2015. p. 555–559. Amini, 2016, Statistical modeling of retinal optical coherence tomography, IEEE Trans Med Imag, 35, 1544, 10.1109/TMI.2016.2519439 Chang, 1982, Analysis of the Weibull distribution function, J Appl Mech, 49, 450, 10.1115/1.3162114 Illingworth, 1987, The adaptive hough transform, IEEE Trans Pattern Anal Mach Intell, 9, 690, 10.1109/TPAMI.1987.4767964 Rizon, 2005, Object detection using circular hough transform, Am J Appl Sci, 2, 1606, 10.3844/ajassp.2005.1606.1609 Chung, 2008, A pruning-and-voting strategy to speed up the detection for lines, circles, and ellipses, J Inf Sci Eng, 24, 503 Yang, 2001, Modified hough transforms for object feature extraction, J Inf Sci Eng, 17, 133 Canny, 1986, A computational approach to edge detection, IEEE Trans Pattern Anal Mach Intell, 8, 679, 10.1109/TPAMI.1986.4767851 Kim G, Xing EP, Fei-Fei L, Kanade T. Distributed cosegmentation via submodular optimization on anisotropic diffusion. In: Proc. ICCV ’11 Proceedings of the 2011 IEEE International Conference on Computer Vision. Barcelona, Spain; 2011. p. 169–76. Zhang L, Gu Z, Li H. SDSP: a novel saliency detection method by combining simple priors. In: Proc. ICIP ‘13 Proceedings of the 2013 IEEE International Conference on Image Processing. Melbourne, Australia; 2013. p. 171–75. Minervini, 2014, Image-based plant phenotyping with incremental learning and active contours, Ecol Inform, 23, 35, 10.1016/j.ecoinf.2013.07.004