Algoritma Interest Point dalam segmentasi citra objek kendaraan
DOI:
https://doi.org/10.33387/protk.v7i1.1353Keywords:
pengolahan citra, kecerdasan buatan, interest point, segmentasi citra, deteksi kendaraanAbstract
Penelitian ini mengumpulkan data berupa gambar dan video yang berisi objek kendaraan di lalu lintas. Data tersebut kemudian akan diproses menggunakan  algoritma pengolahan citra dan dikombinasikan dengan algoritma kecerdasan buatan. Penelitian ini akan difokuskan pada pengolahan citra berbasis algoritma hibrid Interest Point jenis Harris yang dapat mengoptimasi segmentasi citra objek. Proses tersebut dilakukan sebab segmentasi citra objek merupakan faktor utama yang mempengaruhi hasil dari sistem. Pada akhirnya sistem akan dirancang untuk menghasilkan informasi baru sesuai dengan alur sistem yang didasarkan pada kebutuhan, antara lain: pengenalan kendaraan, pengklasifikasian kendaraan, perhitungan jumlah kendaraan, dan pergerakan kendaraan.
References
T. N. Nizar, N. Anbarsanti, and A. S. Prihatmanto, “Multi-object tracking and detection system based on feature detection of the intelligent transportation system,†in 2014 IEEE 4th International Conference on System Engineering and Technology (ICSET), 2014, vol. 4, pp. 1–6.
Y. Y. Nguwi and W. J. Lim, “Number Plate Recognition in Noisy Image,†8th IEEE Int. Congr. Image Signal Process., no. Cisp, pp. 476–480, 2015.
I. EL Jaafari, M. EL Ansari, L. Koutti, A. Ellahyani, and S. Charfi, “A Novel Approach for On-road Vehicle Detection and Tracking,†Int. J. Adv. Comput. Sci. Appl., vol. 7, no. 1, 2016.
Z. Khalid, A. Mazoul, and M. El Ansari, “A new vehicle detection method,†Int. J. Adv. Comput. Sci. Appl., vol. 1, no. 3, 2011.
T. Indrabulan, “A Hybrid Recognition Method Through Video Surveillance Using Combined Harris-Edge,†Patria Artha Technol. J., vol. 2, no. 1, pp. 61–66, 2018.
T. Indrabulan and R. Aminuddin, “Optimasi Window pada Deskriptor HOG dan SVM untuk Klasifikasi Kendaraan dalam Survei Arus Lalu Lintas,†J. INSTEK (Informatika Sains dan Teknol., vol. 3, no. 1, pp. 61–70, 2018.
I. Nurtanio, “Classifying Cyst and Tumor Lesion Using Support Vector Machine Based on Dental Panoramic Images Texture Features,†Feb. 2013.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- The copyright of the accepted for publication articles shall be assigned to Protek : Jurnal Ilmiah Teknik Elektro as the publisher of the journal. The intended copyright includes the rights to publish articles in various forms (including reprints).
- Protek : Jurnal Ilmiah Teknik Elektro maintain the publishing rights of the published articles.
- Authors are permitted to republish or disseminate published articles by sharing the link/DOI of the article at Protek : Jurnal Ilmiah Teknik Elektro. Authors are allowed to use their articles for any legal purposes deemed necessary without written permission from Protek : Jurnal Ilmiah Teknik Elektro with an acknowledgment of initial publication to this journal.
Protek : Jurnal Ilmiah Teknik Elektro by Department of Electrical Engineering, Faculty of Engineering, Universitas Khairun
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.






