Real-Time Construction of Fruit Tree Model Based on Images

Yongping Li; Xingyuan Li; Si Tian

doi:10.12973/eurasia.2017.00771a

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Yongping Li ¹ ^* , Xingyuan Li ¹, Si Tian ¹

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¹ Ningbo Dahongying University, CHINA^* Corresponding Author

Abstract

Using the binocular stereo vision system, the branches of citrus trees in natural scene were reconstructed in virtual environment, to help citrus picking robots recognize and evade obstacles in real working scene. During the reconstruction, images were subjected to thinning, pruning, and curve fitting successively. We reduced the computational burden while guaranteeing the model precision. Then, we adopted the principle of modularized modeling and OpenGL for branch reconstruction. It is verified that the method developed in this work provides a route planning criterion and a virtual workplace for the robot's obstacle evading system.

Keywords

thinning
pruning
curve fitting
modularized modeling
real-time modeling

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2017, Volume 13, Issue 7, 4035-4047

https://doi.org/10.12973/eurasia.2017.00771a

Publication date: 19 Jun 2017

Article Views: 2207

Article Downloads: 878

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References

Agrawal, A., Sun, Y., Barnwell, J., & Raskar, R. (2010). Vision-guided robot system for picking objects by casting shadows. International Journal of Robotics Research, 29(2-3), 155-173. doi:10.1177/0278364909353955.
Bo, P., Bartoň, M., Plakhotnik, D., & Pottmann, H. (2016). Towards efficient 5-axis flank cnc machining of free-form surfaces via fitting envelopes of surfaces of revolution. Computer-Aided Design, 79, 1-11. doi:10.1016/j.cad.2016.04.004.
Côté, J. F., Widlowski, J. L., Fournier, R. A., & Verstraete, M. M. (2009). The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar. Remote Sensing of Environment, 113(5), 1067-1081. doi:10.1016/j.rse.2009.01.017.
Decost, B. L., Jain, H., Rollett, A. D., & Holm, E. A. (2016). Computer vision and machine learning for autonomous characterization of am powder feedstocks. JOM, 69(3), 1-10. doi:10.1007/s11837-016-2226-1.
Escamez, G., Sirois, F., Lahtinen, V., Stenvall, A., Badel, A., & Tixador, P., et al. (2016). 3-d numerical modeling of ac losses in multifilamentary mgb2 wires. IEEE Transactions on Applied Superconductivity, 26(3), 1-7. doi:10.1109/TASC.2016.2533024.
Feng, W. W., Kim, B. U., Yu, Y., Peng, L., & Hart, J. (2010). Feature-preserving triangular geometry images for level-of-detail representation of static and skinned meshes. Acm Transactions on Graphics, 29(2), 11. doi:10.1145/1731047.1731049.
Fernandes, R., Armada-Da-Silva, P., Pool-Goudaazward, A., Moniz-Pereira, V., & Veloso, A. P. (2016). Three dimensional multi-segmental trunk kinematics and kinetics during gait: test-retest reliability and minimal detectable change. Gait & Posture, 46, 18-25. doi:10.1016/j.gaitpost.2016.02.007.
Foley, T., & Hanrahan, P. (2011). Spark: modular, composable shaders for graphics hardware. Acm Transactions on Graphics, 30(4), 107. doi:10.1145/2010324.1965002.
Fu, X., Xu, G. J., Li, Z. J., Du, C. L., Han, Z., & Zhang, T., et al. (2015). Three-dimensional reconstruction modeling of the spatial displacement, extent and rotational orientation of undisplaced femoral neck fractures.Medicine, 94(39), e1393. doi:10.1097/MD.0000000000001393.
Gonzálezjosé, R., Escapa, I., Neves, W. A., Cúneo, R., & Pucciarelli, H. M. (2008). Cladistic analysis of continuous modularized traits provides phylogenetic signals in homo evolution. Nature, 453(7196), 775-778. doi:10.1038/nature06891.
Henderson, B. B., Gerber, P. J., Hilinski, T. E., Falcucci, A., Ojima, D. S., & Salvatore, M., et al. (2015). Greenhouse gas mitigation potential of the world’s grazing lands: modeling soil carbon and nitrogen fluxes of mitigation practices. Agriculture Ecosystems & Environment, 207, 91-100. doi:10.1016/j.agee.2015.03.029.
Jacob, R. E., Colby, S. M., Kabilan, S., Einstein, D. R., & Carson, J. P. (2013). In situ casting and imaging of the rat airway tree for accurate 3d reconstruction. Experimental Lung Research, 39(6), 249-57. doi:10.3109/01902148.2013.801535.
Janoos, F., Mosaliganti, K., Xu, X., Machiraju, R., Huang, K., & Wong, S. T. (2009). Robust 3d reconstruction and identification of dendritic spines from optical microscopy imaging. Medical Image Analysis, 13(1), 167-179. doi:10.1016/j.media.2008.06.019.
Jew, D. K., Hendrich, N., & Zhang, J. (2010). Multi sensor fusion of camera and 3d laser range finder for object recognition. IEEE, 236 - 241. doi:10.1109/MFI.2010.5604459.
Jungblut, D., Vlachos, A., Schuldt, G., Zahn, N., Deller, T., & Wittum, G. (2012). Spinelab: tool for three-dimensional reconstruction of neuronal cell morphology. Journal of Biomedical Optics, 17(7), 076007. doi:10.1117/1.JBO.17.7.076007.
Kempthorne, D. M., Turner, I. W., Belward, J. A., Mccue, S. W., Barry, M., & Young, J., et al. (2015). Surface reconstruction of wheat leaf morphology from three-dimensional scanned data. Functional Plant Biology, 42(5), 444-451. doi:10.1071/FP14058.
Kilgard, M. J., & Bolz, J. (2012). Gpu-accelerated path rendering. Acm Transactions on Graphics, 31(6), 1-10. doi:10.1145/2366145.2366191.
Kim, J., & Jeong, I. K. (2014). Single image-based 3d tree and growth models reconstruction. Etri Journal, 36(3), 450-459. doi:10.4218/etrij.14.0113.0069.
Kim, M. (2013). Gpu isosurface raycasting of fcc datasets. Graphical Models, 75(2), 90-101. doi:10.1016/j.gmod.2012.11.001.
Letsch, H. O., & Kjer, K. M. (2011). Potential pitfalls of modelling ribosomal rna data in phylogenetic tree reconstruction: evidence from case studies in the metazoa. BMC Evolutionary Biology, 11(1), 146. doi:10.1186/1471-2148-11-146.
Liang, J., Gong, J., Li, W., & Ibrahim, A. N. (2014). Visualizing 3d atmospheric data with spherical volume texture on virtual globes.Computers & Geosciences, 68, 81-91. doi:10.1016/j.cageo.2014.03.015.
Lindsay, K. A., Maxwell, D. J., Rosenberg, J. R., & Tucker, G. (2007). A new approach to reconstruction models of dendritic branching patterns. Mathematical Biosciences, 205(2), 271. doi:10.1016/j.mbs.2006.08.005.
List, G. F., & Mashayekhi, M. (2016). A modular colored stochastic petri net for modeling and analysis of signalized intersections. IEEE Transactions on Intelligent Transportation Systems, 17(3), 701-713. doi:10.1109/TITS.2015.2483324.
Mateo, L., Zaro, J., Nchez Navarro, J., ngel, Garc, & A Gil, A., et al. (2014). 3d-geological structures with digital elevation models using gpu programming. Computers & Geosciences, 70(C), 138-146. doi:10.1016/j.cageo.2014.05.014.
Mccraig, M. A., Osinski, G. R., Cloutis, E. A., Flemming, R. L., Izawa, M. R. M., & Reddy, V., et al. (2017). Fitting the curve in excel®; systematic curve fitting of laboratory and remotely sensed planetary spectra. Computers & Geosciences, 100, 103-114. doi:10.1016/j.cageo.2016.11.018.
Méndez, V., Rosell-Polo, J. R., Sanz, R., Escolà, A., & Catalán, H. (2014). Deciduous tree reconstruction algorithm based on cylinder fitting from mobile terrestrial laser scanned point clouds. Biosystems Engineering, 124(4), 78-88. doi:10.1016/j.biosystemseng.2014.06.001.
Menon, J., Ma, Y. L. S., Hewitt, W. T., Science, C., Styner, M., & Gerig, G., et al. (2011). Direct trimming of nurbs surfaces on the gpu. Acm Transactions on Graphics, 28(3), 1. doi:10.1145/1531326.1531353.
Meseguer, A. S., Lobo, J. M., Ree, R., Beerling, D. J., & Sanmartín, I. (2015). Integrating fossils, phylogenies, and niche models into biogeography to reveal ancient evolutionary history: the case of hypericum (hypericaceae). Systematic Biology, 64(2), 215-32. doi:10.1093/sysbio/syu088.
Morrison, C., Huckvale, K., Corish, B., Dorn, J., Kontschieder, P., & Hara, K., et al. (2016). Assessing multiple sclerosis with kinect: designing computer vision systems for real-world use. Human-Computer Interaction, 31(3-4), 191-226. doi:10.1080/07370024.2015.1093421.
Mossel, E., Roch, S., & Sly, A. (2011). Robust estimation of latent tree graphical models: inferring hidden states with inexact parameters. IEEE Transactions on Information Theory, 59(7), 4357-4373. doi:10.1109/TIT.2013.2251927.
Pulli, K., Baksheev, A., Kornyakov, K., & Eruhimov, V. (2012). Real-time computer vision with opencv. Communications of the Acm, 55(6), 61-69. doi:10.1145/2184319.2184337.
Raveh, D. E., & Zaide, A. (2006). Numerical simulation and reduced-order modeling of airfoil gust response. Aiaa Journal, 44(8), 1826-1834. doi:10.2514/1.16995.
Sati, M., Rossignac, J., Seidel, R., Wyvill, B., & Musuvathy, S. (2016). Average curve of n smooth planar curves. Computer-Aided Design, 70(C), 46-55. doi:10.1016/j.cad.2015.06.017.
Schmitt, M., Shahzad, M., & Zhu, X. X. (2015). Reconstruction of individual trees from multi-aspect.
Shi, B. Q., Liang, J., & Liu, Q. (2011). Adaptive simplification of point cloud using k k mathcontainer loading mathjax -means clustering.Computer-Aided Design, 43(8), 910-922. doi:10.1016/j.cad.2011.04.001.
Skalski, J. R., Townsend, R. L., & Gilbert, B. A. (2015). Calibrating statistical population reconstruction models using catch-effort and index data. Journal of Wildlife Management, 71(4), 1309–1316. doi:10.2193/2005-707.
Song, B., Wang, Z., & Sheng, L. (2016). A new genetic algorithm approach to smooth path planning for mobile robots. Assembly Automation, 36(2), 138-145. doi:10.1108/AA-11-2015-094.
Štefan Kohek, & Strnad, D. (2015). Interactive synthesis of self-organizing tree models on the gpu. Computing, 97(2), 145-169. doi:10.1007/s00607-014-0424-7.
Tan, Z., Jamdagni, A., He, X., Nanda, P., Liu, R. P., & Hu, J. (2015). Detection of denial-of-service attacks based on computer vision techniques. IEEE Transactions on Computers, 64(9), 2519-2533. doi:10.1109/TC.2014.2375218.
Tang, S., Dong, P., & Buckles, B. (2013). Three-dimensional surface reconstruction of tree canopy from lidar point clouds using a region-based level set method. International Journal of Remote Sensing, 34(4), 1373-1385. doi:10.1080/01431161.2012.720046.
Tomosar data. Remote Sensing of Environment, 165(2015), 175-185. doi:10.1016/j.rse.2015.05.012.
Urrutia, R. B., Lara, A., Villalba, R., Christie, D. A., Quesne, C. L., & Cuq, A. (2011). Multicentury tree ring reconstruction of annual streamflow for the maule river watershed in south central chile. Water Resources Research, 47(6), 179-187. doi:10.1029/2010WR009562.
Vankipuram, M., Kahol, K., Mclaren, A., & Panchanathan, S. (2010). A virtual reality simulator for orthopedic basic skills: a design and validation study. Journal of Biomedical Informatics, 43(43), 661-668. doi:10.1016/j.jbi.2010.05.016.
Wang, Y., Sibeck, D. G., Merka, J., Boardsen, S. A., Karimabadi, H., & Sipes, T. B., et al. (2013). A new three-dimensional magnetopause model with a support vector regression machine and a large database of multiple spacecraft observations. Journal of Geophysical Research-Space Physics, 118(5), 2173-2184. doi:10.1002/jgra.50226.
Wang, B., & Pai, D. K. (2012). Adaptive image-based intersection volume. Acm Transactions on Graphics, 31(4), 1-9. doi:10.1145/2185520.2185593.
Wright, W. E., Guan, B. T., Tseng, Y. H., Cook, E. R., Wei, K. Y., & Chang, S. T. (2015). Reconstruction of the springtime East Asian subtropical jet and western pacific pattern from a millennial-length taiwanese tree-ring chronology. Climate Dynamics, 44(5-6), 1645-1659. doi:10.1007/s00382-014-2402-3.
Yang, Z., Shen, L. Y., Yuan, C. M., & Gao, X. S. (2015). Curve fitting and optimal interpolation for cnc machining under confined error using quadratic b-splines. Computer-Aided Design, 66(C), 62-72. doi:10.1016/j.cad.2015.04.010.
Zeng, M., Zhao, F., Zheng, J., & Liu, X. (2013). Octree-based fusion for realtime 3d reconstruction. Graphical Models, 75(3), 126-136. doi:10.1016/j.gmod.2012.09.002.
Zhang, T., Zhang, R., Yuan, Y., Gao, Y., Wei, W., & Diushen, M., et al. (2015). Reconstructed precipitation on a centennial timescale from tree rings in the western Tien Shan Mountains, central asia. Quaternary International, 358, 58-67. doi:10.1016/j.quaint.2014.10.054.

How to cite this article

APA

Li, Y., Li, X., & Tian, S. (2017). Real-Time Construction of Fruit Tree Model Based on Images. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 4035-4047. https://doi.org/10.12973/eurasia.2017.00771a

Vancouver

Li Y, Li X, Tian S. Real-Time Construction of Fruit Tree Model Based on Images. EURASIA J Math Sci Tech Ed. 2017;13(7):4035-47. https://doi.org/10.12973/eurasia.2017.00771a

AMA

Li Y, Li X, Tian S. Real-Time Construction of Fruit Tree Model Based on Images. EURASIA J Math Sci Tech Ed. 2017;13(7), 4035-4047. https://doi.org/10.12973/eurasia.2017.00771a

Chicago

Li, Yongping, Xingyuan Li, and Si Tian. "Real-Time Construction of Fruit Tree Model Based on Images". Eurasia Journal of Mathematics, Science and Technology Education 2017 13 no. 7 (2017): 4035-4047. https://doi.org/10.12973/eurasia.2017.00771a

Harvard

Li, Y., Li, X., and Tian, S. (2017). Real-Time Construction of Fruit Tree Model Based on Images. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), pp. 4035-4047. https://doi.org/10.12973/eurasia.2017.00771a

MLA

Li, Yongping et al. "Real-Time Construction of Fruit Tree Model Based on Images". Eurasia Journal of Mathematics, Science and Technology Education, vol. 13, no. 7, 2017, pp. 4035-4047. https://doi.org/10.12973/eurasia.2017.00771a