Sistem Pelacakan Objek Menggunakan Kombinasi Algoritma Optical Flow dan Template Matching

DOI: https://doi.org/10.14710/jtsiskom.6.1.2018.13-17
Open Access Copyright (c) 2018 Jurnal Teknologi dan Sistem Komputer
Article Info
Submitted: 2017-12-05
Published: 2018-01-31
Section: Articles
Language: ID

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This study is aimed to develop a tracking system algorithm by combining optical flow and template matching algorithms to strengthen tracking and minimize the resulting errors. The system has been tested on a football video game with the ball as a tracking object. The optical flow and template matching algorithms are used interchangeably based on the coordinates of both ranges calculated using the Euclidean distance equation. The result shows that the system is able to do tracking, although it is temporarily blocked by other objects, more stable and the distance error between the coordinates of the tracking result and the actual coordinates is not more than 110 pixels compared to using only optical flow or template matching algorithm.

Penelitian ini bertujuan mengembangkan algoritma sistem pelacakan dengan cara menggabungan algoritma optical flow dan template matching untuk memperkuat pelacakan dan memperkecil galat yang dihasilkan. Sistem telah diujikan pada video permainan sepak bola dengan bola sebagai objek yang dilacak. Algoritma optical flow dan template matching digunakan secara bergantian berdasarkan koordinat jarak keduanya yang dihitung menggunakan persamaan jarak Euclidean. Hasil yang diperoleh menunjukkan sistem dapat melakukan palacakan meskipun terhalang sesaat oleh objek lain dan lebih stabil serta galat jarak antara koordinat hasil pelacakan dan koordinat sebenarnya tidak lebih dari 110 piksel dibandingkan hanya menggunakan algoritma optical flow atau template matching saja.

Keywords

Tracking;object;optical flow;template matching

References

  1. S. Shirgeri, P. U. Naik, G. R. Udupi, and G. A. Bidkar, "Design and Development of Optical Flow Based Moving Object Detection and Tracking (OMODT) System," International Journal of Computational Engineering Research, vol. 03, no. 4, pp. 65-72, 2013.
  2. M. Sahasri, C. Gireesh, "Object Motion Detection and Tracking for Video Surveilance," International Journal of Engineering Trends and Technology (IJETT)., Special Issue, pp. 161-164, April 2017.
  3. A. Salhi, and A. Y. Jammoussi, "Object Tracking System using Camshift, Meanshift and Kalman Filter," International Journal Of Electronics And Communication Engineering, vol. 6, no.4, pp. 421-426, 2012.
  4. A. Fahriannur, R. Mardiyanto, and D. Purwanto, "Sistem Tracking Obyek Menggunakan Kamera untuk Aplikasi Target Locking," in Proceeding the 14th Seminar on Intelligent technology And Its Applications, 24 September 2013, Surabaya, 2013.
  5. L. Dan, J. Dai-Hong, B. Rong, Z. Wen-Jing, Z. Wen-Jing, and W. Chao, "Moving Object Tracking Method Based on Improved Lucas-Kanade Sparse Optical Flow Algorithm," in 2017 International Smart Cities Conference (ISC2), 14-17 September 2017, Wuxi, China, 2017.
  6. C. Xiu, and X. Pan, "Tracking Algorithm Based On The Improved Template matching," in 2017 Chinese Control and Decision Conference (CCDC), 28-30 Mei 2017, Chongqing, China, 2017.
  7. S. Battiato, G. M. Farinella, A. Furnari, G. Puglisi, A. Snijders, and J. Spiekstra. “Vehicle Tracking Based on Customized Template Matching," in 2014 International Conference on Computer Vision Theory and Applications (VISAPP), 5-8 Januari 2014, Lisbon, Portugal, 2014.
  8. M. Lalonde, S. Foucher, L. Gagnon, E. Pronovost, M. Derenne, and A. Janelle, "A System to Automatically Track Humans and Vehicles with a PTZ Camera," in SPIE Defense & security : Visual information Processing XVI, 10 April 2007, Orlando, Florida, USA, 2007.
  9. N. Prabhakar, V. Vaithiyanathan, A. P. Sharma, and A. Singh, "Object Tracking using Frame Difference and Template Matching," Research Journal of Applied Sciences, Engineering and Technology, vol. 4, no. 24, pp. 5497-5501, 2012.
  10. E. Parrila, D. Ginestar, J. L. Hueso, J. Riera, and J. R. Torregrosa, "Handling Occlusion in Optical Flow Algorithm for Object Tracking," Computers & Mathematics with Application, vol. 56, no. 3, pp. 733-742, 2008.
  11. N. Nidhi, "Image Processing and Object Detection," International Journal of Applied Research, vol. 1, no. 9, pp. 396-399, 2015.
  12. M. S. Kalas, "Real Time Face Detection and Tracking Using OpenCV," International Journal of Soft Computing and Artificial Intelligence, vol. 2, no.1, pp. 41-44, 2014.
  13. B. Tharanidevi, R. Vadivu, and K. B. Sethupathy, "Moving Object Tracking Distance and Velocity Determination Based on Background Subtraction Algorithm," IOSR Journal of Electronics and Communication Engineering, vol. 8, no. 1, pp. 61-66, 2013.
  14. M. Sharma, and A. Batra, "Analysis of Distance Measures in Content Based Image Retrieval," Global Journal Of Computer Science and Technology, vol. 14, no. 2, pp. 11-16, 2014.
  15. J. C. Elizondo-Leal, E. F. Parra-González, and J. G. Ramírez-Torres, "The Exact Euclidean Distance Transform: A New Algorithm for Universal Path Planning," International Journal of Advanced Robotic System, vol. 10, no. 6, pp. 1-10, 2013.

  1. Ahmad Fahriannur  Scholar
    Politeknik Negeri Jember, Indonesia
  2. Ronny Mardiyanto  Scholar
    Institut Teknologi Sepuluh Nopember Surabaya, Indonesia
  3. Meilana Siswanto  Scholar
    Politeknik Negeri Jember, Indonesia