* Corresponding Author
Hide
Show all
Sistem Pendeteksi dan Pelacakan Bola dengan Metode Hough Circle Transform, Blob Detection, dan Camshift Menggunakan AR.Drone
https://doi.org/10.22146/ijeis.15405 Elki Muhamad Pamungkas(1*), Bakhtiar Alldino Ardi Sumbodo(2), Ika Candradewi(3)
(1) Universitas Gadjah Mada
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(3) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
Parrot AR.Drone is one type of quadrotor UAV. Quadrotor is operated manually with remote control and automatically using GPS (Global Positioning System), but using GPS in tracking mission an object has disadvantage that can’t afford quadrotor position relative to object. Quadrotor require other control methods to perform object tracking. One approach is utilize digital image processing. In this research is designed detection and tracking ball system with digital image processing using OpenCV library and implemented on platform Robot Operating System. The methods which used is hough transform circle, blob detection and camshif.
The results of this research is system on AR.Drone capable of detecting and tracking ball. Based on the test results it was concluded that the maximum distance of system is capable to detecting ball with diameter of 20 cm using hough transform circle method is 500 cm and using blob detection method is 900 cm. Average time detection process to detect the ball using hough transform circle that is 0.0054 second and for blob detection method is 0.0116 second. The success rate of tracking the ball using camshift method from the results of detection hough circle transfom is 100% while from result of detection blob detection is 96.67%
Keywords
Full Text:
PDFReferences
[1] H.Chao, Y. Cao, and Y.Chen, 1995,Autopilots for Small Unmanned Aerial Vehicles: A Survey, International Journal of Control, Automation, and System, 1995.
[2] S.D. Handford, 2005, A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle, The Pennsylvania State University, University Park,PA.
[3] Ritya L., Andriana G., Indah G., 2005, Pengendalian AR Drone 2.0 dan Pengambilan Data Citra Berdasarkan Koordinat GPS, Universitas Telkom, Bandung.
[4] Culjak, I., Abram, D., Pribanic, T., Dzapo, H. dan Cifrek, M., 2012, A brief introduction to OpenCV, MIPRO, 2012 Proceedings of the 35th International Convention, Croatia, May 21-25.
[5] Nagataries, D., Hardiristanto, S., Purnomo, M.H., 2012, Deteksi Objek pada Citra Digital Menggunakan Algoritma Genetika untuk Studi Kasus Sel Sabit.
[7] Ataka A., 2014, ROS, Satu Langkah Menuju Pemrograman Robot yang Lebih Mudah, http://ieeesb.ft.ugm.ac.id/ros-satu-langkah-menuju-pemrograman-robot-yang-lebih-mudah/, diakses pada 11 Ferbuari 2015.
[8] Weickert, J., 2001, Image Processing and Computer Vision. [Online]. Available from: http://books.google.com/books?id=eSu5I9pU3rUC&pgis=1.
[9] Deepthi, R. dan Sankaraiah, S., 2011, Implementation of mobile platform using Qt and OpenCV for image processing applications, Open Systems (ICOS), 2011 IEEE …. [Online] 284–289. Available from: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6079235
[10] Bradski, G., dan Kaehler, A. (2008). Learning OpenCV: Computer Vision with the OpenCV=Library. OReilly Media Inc (Vol. 1) .doi:10.1109/MRA.2009.933612
DOI: https://doi.org/10.22146/ijeis.15405
Article Metrics
Abstract views : 4885
| 
views : 3862
Refbacks
- There are currently no refbacks.
Copyright (c) 2017 IJEIS - Indonesian Journal of Electronics and Instrumentation Systems
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1