PENDETEKSIAN OBJEK ROKOK PADA VIDEO BERBASIS PENGOLAHAN CITRA DENGAN MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER

Kadek Oki Sanjaya, Gede Indrawan, Kadek Yota Ernanda Aryanto

Abstract


Object detection is a topic widely studied by the scientists as a special study in image processing. Although applications of this topic have been implemented, but basically this technology is not yet mature, futher research is needed to developed to obtain the desired result. The aim of the present study is to detect cigarette objects on video by using the Viola Jones method (Haar Cascade Classifier). This method known to have speed and high accuracy because of combining some concept (Haar features, integral image, Adaboost, and Cascade Classifier) to be a main method to detect objects. In this research, detection testing of cigarettes object is in samples of video with the resolution 160x120 pixels, 320x240 pixels, 640x480 pixels under condition of on 1 cigarette object and condition 2 cigarettes object. The result of this research indicated that percentage of average accuracy highest 93.3% at condition 1 cigarette object and 86,7% in the condition 2 cigarette object that was detected on the video with resolution 640x480 pixels, while the percentage of accuracy lowest 90% at condition 1cigarette object, and 81,7% at the condition 2 cigarette objects, detected on the video with the lowest resolution 160x120 pixels. The percentage of average errors at detection cigarettes object was inversely with percentage of accuracy. So that the detection system is able to better recognize the object of the cigarette, then the number of samples in the database needs to be improved and able to represent various types of cigarettes under various conditions and can be added new parameters related to cigarette object

Full Text:

PDF

References


Amalga, SG. 2015. http://repository.unpas.ac.id/26827/6/.(diakses pada tanggal 10 januari 2017).

Anaconda. 2017. https://anaconda.org/anaconda/spyder. (diakses pada tanggal 6 Januari 2017).

Arihutomo, Mukhlas. 2010. “Rancang Bangun Sistem Penjejakan Objek Menggunakan Metode Viola Jones Untuk Aplikasi EyeBot”. http://repo.pens.ac.id/311/1/1151.pdf. (diakses tanggal 5 Januari 2017).

Baser, Ekrem. 2016. “Detection and Classification Of Vehicles In Traffic By Using Haar Cascade Classifier”, Proceedings of 58th ISERD International Conference, Prague, Czech Republic, 23rd-24th December 2016, www.worldresearchlibrary.org/up_proc/pdf/578-1486634118 19-22.pdf. (diakses tanggal 8 Januari 2017).

Doxygen. 2012. http://docs.opencv.org/trunk/d7/d8b/ tutorial_py_face_detection.html. (diakses tanggal 6 Januari 2017).

Harrison. 2017. https://pythonprogramming.net/haar-cascade-object-detection-python-opencv-tutorial/. (diakses tanggal 6 Januari 2017).

Hestiningsih, I. 2008. Pengolahan Citra. http://toba.mytoba.com/dl/Pengolahan% 20Citra.pdf. (diakses tanggal 4 Januari 2017).

Kurniawan, Agus. 2009. “Aplikasi Absensi Kuliah Berbasis Identifikasi Wajah Menggunakan Metode Gabor Wavelet” Makalah Skripsi Institut Teknologi Sepuluh Nopember (ITS) Surabaya, Surabaya.

Mahmudi, Ali dan M. Taufiqur Rusda. 2014. “Deteksi Senjata Tajam dengan metode Haar Cascade Classifier Menggunakan Teknologi SMS Gateway”. https://www.academia.edu/. (diakses tanggal 3 Januari 2017).

Muhaimin, Syahlan. 2013. “Rancang Bangun Aplikasi Multi-Face Detector menggunakan Metode Viola Jones pada Face Recognitioon”. http://repository.uin-suska.ac.id/1220 /1/2013 _2013126TIF.pdf. (diakses tanggal 6 Januari 2017).

Mulyawati, Anizsah dan Chaerunisai Bahar. 2014. “Metode Viola-Jones untuk Mendeteksi Jenis dan Jumlah Kendaraan dalam Intelligent Transport System”. Makalah Skripsi Jurusan Teknik Elektro Universitas Hasanuddin. Makassar.

Munir, Rinaldi. 2004. Pengolahan Citra Digital. Bandung: Unit Penerbitan Informatika Bandung.

Padilla, R. 2012. “Evaluation of Haar Cascade Classifiers Designed for Face Detection”. International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:6, No:4, 2012.

Priawadi. 2012. http://www.priawadi.com/2012/09/ opencv.html. (diakses pada tanggal 5 April 2017).

Reinius, Staffan. 2013. “Object Recognition using the OpenCV Haar Cascade-Classifier on the iOS platform”. http://www.diva-portal.org/smash/get/diva2:601707/fulltext 01.pdf. (diakses pada tanggal 6 Januari 2017).

Robin. 2013. http://coding-robin.de/2013/07/22/train-your-own-opencv-haar-classifier.html (diakses pada tanggal 5 Januari 2017).

Santoso, Hadi dan Agus Harjoko. 2013. Haar Cascade Classifier dan Algoritma untuk Deteksi Banyak Wajah dalam Ruang Kelas. Jurnal Teknologi, Volume 6 Nomor 2, hlm 108-115.

Seo, Naotoshi. 2007. Tutorial: OpenCV haartraining (Rapid Object Detection with A Cascade of Boosted Classifiers Based on Haar-like Feature). http://note.sonots.com/SciSoftware/ haartraining.html. (diakses pada tanggal 10 Januari 2017).

Soo, Sander. 2014. “Object detection using Haar-cascade Classifier”, http://ds.cs.ut.ee/Members/artjom85/2014dss-course-media/Object%20detection%20using%20Haar-final. pdf. (diakses pada tanggal 7 Januari 2017).

Taurisna, Afnisyah. 2009. Analisis Pengaruh Kualitas Citra terhadap Kinerja Metode Pendeteksi Tepi. http://repository.usu.ac.id/handle/123456789/7873. (diakses pada tanggal 7 Januari 2017.

Viola, Paul and Michael Jones. 2001. “Rapid Object Detection using a Boosted Cascade of Simple Features”. Proceedings of the 2001, IEEE Computer Society Conference on, 2001, vol. 1, pp. I–511.

Yildirim, Mustafa E. 2014. “Gender Classification Based on Binary Haar Cascade”, International Journal of Computer and Communication Engineering, Vol. 3, No. 2, Maret 2014.




DOI: http://dx.doi.org/10.23887/ijnse.v1i3.12938

Article Metrics

Abstract view : 1810 times
PDF file view : 1550 times

Refbacks

  • There are currently no refbacks.



International Journal of Natural Science and Engineering indexed by:

  Akreditasi SINTA 5 Crossref    




Creative Commons License

International Journal of Natural Science and Engineering is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.