Temu Kembali Berbasis Citra untuk Menemukan Kemiripan Merek Menggunakan Algoritma SIFT dan SURF
DOI:
https://doi.org/10.24002/jbi.v13i02.6328Keywords:
Merek, SIFT, SURF, K-Nearest Neighbors, Euclidean, Trademark, SIFT, SURF, K-Nearest Neighbors, EuclideanAbstract
Abstract. Image-Based Retrieval to Find Trademark Similarities Using SIFT and SURF Algorithms. In the world of trade in products and services, brands are essential. Every company wants to register a unique trademark for its products and services. Registration and evaluation to find the uniqueness of a trademark is challenging. Trademark image registration is one of the critical application areas of Content-BasedRetrieval (CBIR), which compares new brands with existing ones to ensure no dispute in the community. This study used SIFT and SURF algorithms to build a content-based brand image retrieval system. The research data used trademark data dispute cases that were decided in court. The features extracted from the SIFT and SURF algorithms are used to find similarities between the query image and the image in the database. Furthermore, the k-Nearest Neighbors algorithm with Euclidean distance measurements was used to sort the database images that were most similar to the query image. Experiments were conducted to find the algorithm and sequencing with the highest precision and recall values.
Keywords: Trademark, SIFT, SURF, K-Nearest Neighbors, Euclidean.
Abstrak. Dalam dunia perdagangan produk dan jasa, merek menjadi sangat penting. Setiap perusahaan ingin mendaftarkan merek dagang yang unik untuk produk dan jasanya. Pendaftaran dan evaluasi untuk menemukan kekhasan suatu merek dagang menjadi suatu pekerjaan yang sangat sulit. Pendaftaran citra merek dagang adalah salah satu area aplikasi penting Content Based Information Retrieval (CBIR) yang membandingkan merek baru dengan merek yang ada untuk memastikan tidak ada sengketa di masyarakat. Penelitian ini menggunakan algoritma SIFT dan SURF untuk membangun sistem temu kembali citra merek berbasis konten . Data penelitian menggunakan kasus sengketa data merek yang diputuskan di pengadilan. Fitur hasil ekstraksi algoritma SIFT dan SURF
digunakan untuk mencari kemiripan citra query dan citra dalam basis data. Selanjutnya algoritma k-Nearest Neighbors dengan pengukuran jarak Euclidean digunakan untuk mengurutkan citra basis data yang paling mirip dengan citra query. Eksperimen dilakukan untuk mengetahui algoritma dan pengurutan dengan nilai presisi dan recall tertinggi.
Kata Kunci: Merek, SIFT, SURF, K-Nearest Neighbors, Euclidean.
References
M. Fajar, Y. Nurhayati, and I. Ifrani, “Iktikad Tidak Baik Dalam Pendaftaran Dan Model Penegakan Hukum Merek Di Indonesia,” Jurnal Hukum Ius Quia Iustum, vol. 25, no. 2, pp. 219–236, May 2018, doi: 10.20885/iustum.vol25.iss2.art1.
W. Wijaya and C. S. T. Kansil, “Analisis Kekuatan Unsur Itikad Baik Pada Pelaksanaan Pendaftaran Merek Di Indonesia (Studi Kasus Putusan Mahkamah Agung Nomor 364k/Pdt.Sus-Hki/2014) Berdasarkan Undang-Undang Nomor 20 Tahun 2016,” Jurnal Hukum Adigama, vol. 1, no. 1, p. 937, 2018, doi: 10.24912/adigama.v1i1.2181.
M. Kholil, A. Sulistiyono, and A. S. Sudarwanto, “Issues and Challenges of Trademark Law Registration for Small,” International Journal of Business, Economics and Law, Vol. 18, Issue 5 (April), vol. 18, no. 5, pp. 311–319, 2019.
Z. C. X. Wang, “Trademark Image Retrieval System Based on SIFT Algorithm,” in IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS), 2018, pp. 740–743.
F. Mohd Anuar, R. Setchi, and Y. K. Lai, “Trademark image retrieval using an integrated shape descriptor,” Expert Syst Appl, vol. 40, no. 1, pp. 105–121, 2013, doi: 10.1016/j.eswa.2012.07.031.
L. Pinjarkar and M. Sharma, “Content Based Image Retrieval for Trademark Registration : A Survey,” International Journal of Advanced Reserach in Computer and Communication Engineering, vol. 2, no. 11, pp. 4424–4430, 2013.
J. P. Eakins, K. Shields, and J. Boardman, “ARTISAN - a shape retrieval system based on boundary family indexing,” in Proceedings Volume 2670, Storage and Retrieval for Still Image and Video Basis datas IV, 1996, vol. 2670117. doi: https://doi.org/10.1117/12.234792.
R. D. A. A. M. Baresi Ariel, “Implementasi Metode Speed Up Robust Feature dan,” vol. 3, no. 4, pp. 178–186, 2016.
A. D. Narhare and G. V. Molke, “Trademark detection using SIFT features matching,” in Proceedings - 1st International Conference on Computing, Communication, Control and Automation, ICCUBEA 2015, Jul. 2015, pp. 684–688. doi: 10.1109/ICCUBEA.2015.140.
R. K. Tripathi and S. C. Agrawal, “A shape and texture features fusion to retrieve similar Trademark Image Material,” IOP Conf Ser Mater Sci Eng, vol. 1116, no. 1, p. 012026, 2021, doi: 10.1088/1757-899x/1116/1/012026.
R. M. Akbar and N. Sunarmi, “Pengenalan Barang Pada Kereta Belanja Menggunakan Metode Scale Invariant Feature Transform (SIFT),” Jurnal Mantap, vol. 5, no. 6, 2018, doi: 10.25126/jtiik.201851046.
M. M. Efendi and E. Wahyudi, “Metode Algoritma SIFT dan Histogram Color RGB Untuk Analisis Manipulasi Copy-Move pada Citra Digital” Jurnal Explore STMIK Mataram , vol. 9, no. 1, pp. 31–35, 2019.
M. S. Lubis, A. A. Zahra, and I. Santoso, “Deteksi Pemalsuan Copy-Move Pada Citra Digital Menggunakan Scale Invariant Feature Transform ( Sift ) Dan Generalized 2 Nearest-Neighbor ( G2Nn ),” Transient: Jurnal Ilmiah Teknik Elektro ,vol. 8, no. 2, pp. 158–164, 2019..
A. D. Narhare and G. V. Molke, “Trademark detection using SIFT features matching,” in Proceedings - 1st International Conference on Computing, Communication, Control and Automation, ICCUBEA 2015, Jul. 2015, pp. 684–688. doi: 10.1109/ICCUBEA.2015.140.
Najeeb Ur Rehman Malik, auAwais G. Airij, S. A. Memon, Y. N. Panhwar, S. A. R. Abu-Bakar, and M. A. El-Khoreby, “Performance Comparison Between SURF and SIFT for Content-Based Image Retrieval,” in Proc. of the 2019 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2019, 2019, pp. 216–218.
S. Bekhet and A. Ahmed, “Evaluation of similarity measures for video retrieval,” Multimed Tools Appl, vol. 79, no. 9–10, pp. 6265–6278, 2020, doi: 10.1007/s11042-019-08539-4.
D. G. Lowe, “Object Recognition from Local Scale-Invariant Features,” in Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999, 1999, vol. 2, pp. 1150–1157. doi: 10.1109/ICCV.1999.790410.
D. G. Low, “Distinctive image features from scale-invariant keypoints,” Int J Comput Vis, pp. 91–110, 2004.
P. Loncomilla, J. Ruiz-del-Solar, and L. Martínez, “Object recognition using local invariant features for robotic applications: A survey,” Pattern Recognit, vol. 60, pp. 499–514, 2016, doi: 10.1016/j.patcog.2016.05.021.
T. He, Y. Wei, Z. Liu, G. Qing, and D. Zhang, “Content based image retrieval method based on SIFT feature,” Proceedings - 3rd International Conference on Intelligent Transportation, Big Data and Smart City, ICITBS 2018, vol. 2018-Janua, pp. 649–652, 2018, doi: 10.1109/ICITBS.2018.00169.
R. K. Tripathi and S. C. Agrawal, “A shape and texture features fusion to retrieve similar Trademark Image Material,” IOP Conf Ser Mater Sci Eng, vol. 1116, no. 1, p. 012026, 2021, doi: 10.1088/1757-899x/1116/1/012026.
V. T. Syafira, “Perlindungan Hukum Bagi Pemegang Hak Merek Superman Terhadap Pelanggaran Merek,” Jurnal Suara Hukum, vol. 3, no. 1, p. 85, 2021, doi: 10.26740/jsh.v3n1.p85-114.
D. M. W. Powers, “Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation,” Journal of Machine Learning Technologies, Volume 2, Issue 1, pp-37-63, 2011.
M. Arora, U. Kanjilal, and D. Varshney, “Evaluation of information retrieval: precision and recall,” International Journal of Indian Culture and Business Management, vol. 12, no. 2, p. 224, 2016, doi: 10.1504/ijicbm.2016.074482.
M. Martin and L. Nilawati, “Recall dan Precision Pada Sistem Temu Kembali Informasi Online Public Access Catalogue (OPAC) di Perpustakaan,” Paradigma - Jurnal Komputer dan Informatika, vol. 21, no. 1, pp. 77–84, 2019, doi: 10.31294/p.v21i1.5064.
R. R. Pangestu and D. R. Masrur, “Perlindungan Hukum Terhadap Merek Terkenal Ikea (Analisa Putusan Mahkamah Agung Nomor 264 K/Pdt. Sus-Hki/2015),” JCA of Law, 2020.
Irtiyah, Ridha Faulika. "Analisis Yuridis Pertimbangan Hakim Atas Sengketa Kepemilikan Merek Asing Terkenal Berdasarkan Putusan Mahkamah Agung 2018-2020." Jurnal Abdi Ilmu, Vol. 14, no 2, pp: 131-151, 2021.
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