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[4] R. Barth, J. Hemming, and E. J. van Henten, “Design of an Eye-inHand Sensing and Servo Control Framework for Harvesting Robotics in Dense Vegetation”, Biosystems Engineering, Vol. 146, pp. 7184, 2016. http://dx.doi.org/10.1016/j.biosystemseng.2015.12.001.
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[10] G. Feng, C. Qixin, and M. Nagata, “Fruit Detachment and Classification Method for Strawberry Harvesting Robot”, International Journal of Advanced Robotic Systems, Vol. 5, Issue 1, pp. 4148, 2008. https://doi.org/10.5772/5662.
[11] S. Amatya,M. Karkee,Q. Zhang,and M. D. Whiting,“Automated Detection of Branch Shaking Locations for Robotic Cherry Harvesting UsingMachineVision”,Robotics,Vol.6,Issue.4.Pages31,2017 https://doi.org/10.3390/robotics6040031.
[12] S.S. Mehta and T. F. Burks, “Robust Visual Servo Control in the Presence of Fruit Motion for Robotic Citrus Harvesting”, Computers and Electronics in Agriculture, Vol. 123, pp. 362375, 2016. http://dx.doi.org/10.1016/j.compag.2016.03.007.
[13] C. Wang, Y. Tang, X. Zou, W. SiTu, and W. Feng, “A RobustFruit Image Segmentation Algorithm against Varying Illumination for Vision System of Fruit Harvesting Robot”, Optik, Vol. 131, pp. 626-631, 2017. http://dx.doi.org/10.1016/j.ijleo.2016.11.177.
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[16] E. Bugarin and R. Kelly, “Direct Visual Servoing of Planar Manipulators Using Moments of Planar Targets”, Robot Vision, IntechOpen, ed. Ales Ude, 2010. DOI: 10.5772/9297.
[17] M. F. Reis, A. C. Leite, P. J. From, L. Hsu, and F. Lizzaralde, “Visual Servoing for Object Manipulation with a Multifingered Robot Hand”, IFAC-PapersOnLine, Vol. 48, issue. 19, pp. 1-6, 2015.https://doi.org/10.1016/j.ifacol.2015.12.001
[18] N. T. Siebel, D. Peters and G. Sommer, “Models and Control Strategies for Visual Servoing”, Visual Servoing Rong-Fong Fung, IntechOpen, 2010, DOI:10.5772/8550.https://www.scilab.org/, accessed on June 15th, 2018.
[19] J. F. Khan, S. M. A. Bhuiyan, and R. R. Adhami, “Image segmentation and shape analysis for road-sign detection,” IEEETrans.Intell.Transp.Syst, vol. 12, no. 1, pp. 83-96, 2011.
[20] A. Kaspers, “Blob Detection.
[21] M. Dhome, U. Blaise, and P. C. Ii, “Real Time Robust Template Matching,”, 2003.
[2] A. Bala, “An Improved Watershed Image Segmentation Technique Using MATLAB,” Int.J.Sci.Eng.Res, vol. 3, no. 6, p. 1206, 2012.
[3] A. Silwal, A. Gongal, and M. Karkee, “Identification of red apples in field environment with over the row machine vision system, vol. 16, no. 4, pp. 66-75, 2014.
[4] R. Barth, J. Hemming, and E. J. van Henten, “Design of an Eye-inHand Sensing and Servo Control Framework for Harvesting Robotics in Dense Vegetation”, Biosystems Engineering, Vol. 146, pp. 7184, 2016. http://dx.doi.org/10.1016/j.biosystemseng.2015.12.001.
[5] W. Ji et al. 2012 “Automatic Recognition Vision System Guided for Apple Harvesting Robot Computers and Electrical Engineering”, Computers & Electrical Engineering, Vol. 38, No. 5, pp. 11861195.https://doi.org/10.1016/j.compeleceng.2011.11.005
[6] M. Stoelen, K. Krzysztof, V. F. Tejada, N. Heiberg, C. Balaguer, and A. Korsaeth, “Low-Cost Robotics for Horticulture: A Case Study on Automated Sugar Pea Harvesting”, 10th European Conference on Precision Agriculture (ECPA), 2015. DOI: 10.3920/978-90-8686-814-8 34.
[7] T. T. Nguyen, E. Kayacan, J. De Baedemaeker, W. Saeys, “Task and Motion Planning for Apple Harvesting Robot”, IFAC Proceedings Volumes, Vol. 46, Issue. 18, pp. 247-252, 2013. https://doi.org/10.3182/20130828-2-SF-3019.00063.
[8] G. Wang, Y. Yu, and Q. Feng, “Design of End-Effector for Tomato Robotic Harvesting”, IFAC-PapersOnLine, Vo. 49, Issue 16, pp. 190-193, 2016.https://doi.org/10.1016/j.ifacol.2016.10.035
[9] J . Li, M. Karkee, Q. Zhang, K. Xiao, and T. Feng,“Characterizing Apple Picking Patterns for Robotic Harvesting”, Computers and Electronics in Agriculture, Vol. 127, pp.633640, 2016. http://dx.doi.org/10.1016/j.compag.2016.07.024.
[10] G. Feng, C. Qixin, and M. Nagata, “Fruit Detachment and Classification Method for Strawberry Harvesting Robot”, International Journal of Advanced Robotic Systems, Vol. 5, Issue 1, pp. 4148, 2008. https://doi.org/10.5772/5662.
[11] S. Amatya,M. Karkee,Q. Zhang,and M. D. Whiting,“Automated Detection of Branch Shaking Locations for Robotic Cherry Harvesting UsingMachineVision”,Robotics,Vol.6,Issue.4.Pages31,2017 https://doi.org/10.3390/robotics6040031.
[12] S.S. Mehta and T. F. Burks, “Robust Visual Servo Control in the Presence of Fruit Motion for Robotic Citrus Harvesting”, Computers and Electronics in Agriculture, Vol. 123, pp. 362375, 2016. http://dx.doi.org/10.1016/j.compag.2016.03.007.
[13] C. Wang, Y. Tang, X. Zou, W. SiTu, and W. Feng, “A RobustFruit Image Segmentation Algorithm against Varying Illumination for Vision System of Fruit Harvesting Robot”, Optik, Vol. 131, pp. 626-631, 2017. http://dx.doi.org/10.1016/j.ijleo.2016.11.177.
[14] H. Wang and Y. Liu, “Dynamic Visual Servoing with an Uncalibrated Eye-inHand Camera”, Robot Manipulators, IntechOpen, ed. Marco Ceccarelli, 2008. DOI: 10.5772/6222.
[15] T. Dewi, P. Risma, Y. Oktarina, and M. T. Roseno, “Perbandingan Desain dan Pemodelan TanganRobot Lima Jari sebagai Sistem Underactuated”, AnnualResearchSeminar2016, Vol 2, No. 1, pp. 139-145, 2016.
[16] E. Bugarin and R. Kelly, “Direct Visual Servoing of Planar Manipulators Using Moments of Planar Targets”, Robot Vision, IntechOpen, ed. Ales Ude, 2010. DOI: 10.5772/9297.
[17] M. F. Reis, A. C. Leite, P. J. From, L. Hsu, and F. Lizzaralde, “Visual Servoing for Object Manipulation with a Multifingered Robot Hand”, IFAC-PapersOnLine, Vol. 48, issue. 19, pp. 1-6, 2015.https://doi.org/10.1016/j.ifacol.2015.12.001
[18] N. T. Siebel, D. Peters and G. Sommer, “Models and Control Strategies for Visual Servoing”, Visual Servoing Rong-Fong Fung, IntechOpen, 2010, DOI:10.5772/8550.https://www.scilab.org/, accessed on June 15th, 2018.
[19] J. F. Khan, S. M. A. Bhuiyan, and R. R. Adhami, “Image segmentation and shape analysis for road-sign detection,” IEEETrans.Intell.Transp.Syst, vol. 12, no. 1, pp. 83-96, 2011.
[20] A. Kaspers, “Blob Detection.
[21] M. Dhome, U. Blaise, and P. C. Ii, “Real Time Robust Template Matching,”, 2003.
- Abstract viewed - 1593 times
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Affiliations
Muhammad Dede Yusuf
Politeknik Negeri Sriwijaya
RD Kusumanto
Politeknik Negeri Sriwijaya
Yurni Oktarina
Politeknik Negeri Sriwijaya
Tresna Dewi
Politeknik Negeri Sriwijaya
Pola Risma
Politeknik Negeri Sriwijaya
BLOB Analysis for Fruit Recognition and Detection
Abstract
Robot application in agriculture can ease the farming process, especially as the harvesting robot for seasonal fruit that is available in a short time. The addition of "eye" as the image sensor is an important feature for a harvesting robot. Thanks to the increment of technology, the camera is getting smaller with better performance, and lower prices. The cheap sensors and components make the creation of cheap and effective robot possible. Image processing is necessary for object detection, and open source software is available now for this purpose. This paper proposes BLOB analysis for object detection of 5 fruits with different shapes and colors. The simulation results show that the proposed method is effective for object detection regardless the shapes, colors, and noises.