Otomasi Kamera Perangkap Menggunakan Deteksi Gerak dan Komputer Papan Tunggal


Habib Dwi Cahya(1*), Agus Harjoko(2)

(1) Program Studi Elektronika dan Instrumentasi, FMIPA UGM, Yogyakarta
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author


USB camera is currently used in daily life for various purposes. On its development, the use of USB camera can be used to create camara traps and can be used to observe the development of animal with integrated systems. In this research, motion detection was used to observe animals online using Single Board Computer (SBC)

Camera trap in this research using Single Board camera in form of raspberry pi 3 B. Python proggramming language is used with OpenCV library. The method used to detect motion is the Mixture of Gaussian (MOG). The result image gained by motion detection will be uploaded to the dropbox API.

The test performed on 11 videos, the system can process images with 320x240 resolution. The test results show the best blut value of k = 13, the best threshold value is 100 pixel with an accuracy of 80,3%, and the maximum distance system can detect animal objects as far as 6m. The response time gained for the sytem to process frame per second have average of 0,098 seconds, while for uploading image to dropbox han an average of 1,618 seconds. The test result show the system still has room for development and improvement.


camera trap; USB camera; Motion detection; OpenCV; SBC

Full Text:



[1] E. Surendar, V. M. Thomas, and A. M. Posonia, 2016, Animal tracking using background subtraction on multi threshold segmentation, Proc. IEEE Int. Conf. Circuit, Power Comput. Technol. ICCPCT 2016, no. Ccd. [Online]. Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7530223 [Accessed: 30-Mei-2017].

[2] Z. ZHANG, Z. He, G. Cao, and W. Cao, 2016, Animal Detection from Highly Cluttered Natural Scenes Using Spatiotemporal Object Region Proposals and Patch Verification, IEEE Trans. Multimed., vol. 9210, no. c, pp. 1–1. [Online]. Available:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7523423 [Accessed: 30-Mei-2017]

[3] O. Krejcar, 2013, Motion Detection Using a USB Camera, pp. 281–286. [Online]. Available:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6632827 [Accessed: 30-Mei-2017].

[4] A. Mahabalagiri, K. Ozcan, and S. Velipasalar, 2014, Camera motion detection for mobile smart cameras using segmented edge-based optical flow, 11th IEEE Int. Conf. Adv. Video Signal-Based Surveillance, AVSS 2014, pp. 271–276. [Online]. Available:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6918680[Accessed: 30-Mei-2017].

[5] Y. Wu, X. He, and T. Nguyen, 2015, Moving Objects Detection with Freely Moving Camera via Background Motion Subtraction, IEEE Trans. Circuits Syst. Video Technol., vol. PP, no. 99, pp. 1–1. [Online]. Available:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7303924 [Accessed: 30-Mei-2017].

[6] F. Amaluddin, M. A. Muslim, dan A. Naba, "Klasifikasi Kendaraan Menggunakan Gaussian Mixture Model ( GMM ) dan Fuzzy Cluster", Jurnal EECCIS , Vol. 9, no. 1,p. 19–24, 2015 [online]. Available:http://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/269. [Accessed: 30-Mei-2017]

[7] S. Brahmbhatt, 2013 Embedded Computer Vision: Running OpenCV Programs on the Raspberry Pi, Pract. OpenCV, no. 9, vol. 53, 201–218. [online]. Available:http://www.bookmetrix.com/detail/chapter/6e671f63-fb9f-4fed-ae7d-dcb14a5970da#downloads [Accessed: 30-Mei-2017]

[8] S. Manchanda, Analysis of Computer Vision based Techniques for Motion Detection, International Conference - Cloud System and Big Data Engineering (Confluence), No 6, 445–450, 2016 [Online]. Available:http://ieeexplore.ieee.org/document/7508161/. [Accessed : 30-mei-2017]

[9] G. Braedski, dan A. Kaehler, 2008, Learning OpenCV , O'Reilly Media Inc, Gravenstein Highway North [Online]. Available: http://www.bogotobogo.com/cplusplus/files/OReilly%20Learning%20OpenCV.pdf [Accessed: 30-Mei-2017]

[10] A. Nurhopipah, 2017, Deteksi Gerak dan Pengenalan Wajah untuk Sistem Pengawasan Melalui Video CCTV, Tesis, Program Studi S2 Ilmu Komputer, Univ. Gadjah Mada, Yogyakarta.

DOI: https://doi.org/10.22146/ijeis.36102

Article Metrics

Abstract views : 3059 | views : 3510


  • There are currently no refbacks.

Copyright (c) 2019 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Copyright of :
IJEIS (Indonesian Journal of Electronics and Instrumentations Systems)
ISSN 2088-3714 (print); ISSN 2460-7681 (online)
is a scientific journal the results of Electronics
and Instrumentations Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijeis.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijeis

View My Stats1
View My Stats2