Document Validation for Cooperation Agreement Documents at The Undiksha Cooperation and Public Relations Agency (Badan Kerja Sama dan Kehumasan) using Local Binary Pattern (LBP) and YOLOv5 Methods
DOI:
https://doi.org/10.23887/janapati.v12i3.66070Keywords:
document validation, cooperation agreement document, BKK Undiksha, Local Binary Pattern, YOLOv5Abstract
A cooperation agreement document managed by BKK Undiksha is a conventionally managed document. With the implementation of the Kampus Merdeka - Merdeka Belajar curriculum in 2021, the number of incoming cooperation agreement documents has increased rapidly, making the collection of document data much longer and inefficient. Therefore, there is a need for a scheme that can automatically validate collaboration documents. The document validation scheme was developed using the Local Binary Patterns and YOLOv5 methods. The data used in the development is primary data from BKK Undiksha in 2021, where two agencies collaborate. The development result is the document validation model collaboration using the Local Binary Pattern and YOLOv5 methods with the best accuracy results of 95.36%, and the ability of the model to detect the number of seal, stamp and signature components is 90.73%.
References
BKK Undiksha, Data dan Statistik Dokumen Kerja Sama. 2021. [Online]. Available: https://www.bertelsmann-stiftung.de/fileadmin/files/BSt/Publikationen/GrauePublikationen/MT_Globalization_Report_2018.pdf%0Ahttp://eprints.lse.ac.uk/43447/1/India_globalisation%2C society and inequalities%28lsero%29.pdf%0Ahttps://www.quora.com/What-is-the
A. Prasetio and P. M. Hasugian, “Improving the Quality of Digital Images Using the Median Filter Technique to Reduce Noise,” SinkrOn, vol. 4, no. 1, p. 143, Oct. 2019, doi: 10.33395/sinkron.v4i1.10155.
O. Joshua, J. S. Owotogbe, T. S. Ibiyemi, and B. A. Adu, “A Comprehensive Review On Various Types of Noise in Image Processing,” Article in International Journal of Scientific and Engineering Research, 2019, [Online]. Available: http://www.ijser.org
R. K. Riad Al-Taie, B. Jumaa Saleh, and H. A. Abu-Alsaad, “A REVIEW PAPER: DIGITAL IMAGE FILTERING PROCESSING.” [Online]. Available: www.techniumscience.com
M. Miladiah, R. Umar, and I. Riadi, “Implementasi Local Binary Pattern untuk Deteksi Keaslian Mata Uang Rupiah,” Jurnal Edukasi dan Penelitian Informatika (JEPIN), vol. 5, no. 2, p. 197, 2019, doi: 10.26418/jp.v5i2.32721.
N. Anusha and M. Siva Sindhuri, “Analysis of Document Images through Local Binary Patterns,” Indian J Sci Technol, vol. 10, no. 20, pp. 1–6, 2017, doi: 10.17485/ijst/2017/v10i20/73915.
N. Sharma, R. Mandal, R. Sharma, U. Pal, and M. Blumenstein, “Signature and logo detection using deep CNN for document image retrieval,” Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR, vol. 2018-Augus, pp. 416–422, 2018, doi: 10.1109/ICFHR-2018.2018.00079.
U. Nepal and H. Eslamiat, “Comparing YOLOv3, YOLOv4 and YOLOv5 for Autonomous Landing Spot Detection in Faulty UAVs,” Sensors, vol. 22, no. 2, 2022, doi: 10.3390/s22020464.
CBSE Academic, AI Curriculum Handbook. 2019.
I. P. N. Syair, Ayu Sabrina., Muh Ihsan., “Identifikasi citra tanda tangan menggunakan Local Binary Pattern (LBP) pada Smartphone berbasis Android,” semanTIK, vol. 5, no. 1, pp. 17–24, 2019.
F. Cruz, N. Sidere, M. Coustaty, V. P. D’Andecy, and J. M. Ogier, “Local Binary Patterns for Document Forgery Detection,” in Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, IEEE Computer Society, Jan. 2018, pp. 1223–1228. doi: 10.1109/ICDAR.2017.202.
Š. Hubálovský, P. Trojovský, N. Bacanin, and V. K, “Evaluation of Deepfake Detection Using YOLO with Local Binary Pattern Histogram,” PeerJ Comput Sci, vol. 8, p. e1086, Sep. 2022, doi: 10.7717/peerj-cs.1086.
J. Yao, J. Qi, J. Zhang, H. Shao, J. Yang, and X. Li, “A real-time detection algorithm for kiwifruit defects based on yolov5,” Electronics (Switzerland), vol. 10, no. 14, 2021, doi: 10.3390/electronics10141711.
Jupiyandi Saniputra, F. R. Pratama, and Yoga Dharmawan, “Pengembangan Deteksi Citra Mobil Untuk Mengetahui Jumlah Tempat Parkir Menggunakan Cuda Dan Modified Yolo,” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 6, no. 4, pp. 413–419, 2019, doi: 10.25126/jtiik.201961275.
R. Padilla, S. L. Netto, and E. A. B. Da Silva, “A Survey on Performance Metrics for Object-Detection Algorithms,” International Conference on Systems, Signals, and Image Processing, vol. 2020-July, pp. 237–242, 2020, doi: 10.1109/IWSSIP48289.2020.9145130.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Komang Jepri Kusuma Jaya, Made Windu Antara Kesiman, I Made Dendi Maysanjaya
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with Janapati agree to the following terms:- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. (See The Effect of Open Access)
