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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL INTEGRASI JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Applied Electrical Engineering Journal of Community Service and Empowerment Journal of Applied Computer Science and Technology (JACOST) Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Engagement: Jurnal Pengabdian Kepada Masyarakat
Eko Rudiawan Jamzuri
Department Of Electrical Engineering, Politeknik Negeri Batam, Indonesia
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences Other

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Journal : International Journal of Electrical and Computer Engineering

 1 
Automatic optical inspection for detecting keycaps misplacement using Tesseract optical character recognition Anisatul Munawaroh; Eko Rudiawan Jamzuri
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5147-5155

Abstract

This research study aims to develop automatic optical inspection (AOI) for detecting keycaps misplacement on the keyboard. The AOI hardware has been designed using an industrial camera with an additional mechanical jig and lighting system. Optical character recognition (OCR) using the Tesseract OCR engine is the proposed method to detect keycaps misplacement. In addition, captured images were cropped using a predefined region of interest (ROI) during the setup. Subsequently, the cropped ROIs were processed to acquire binary images. Furthermore, Tesseract processed these binary images to recognize the text on the keycaps. Keycaps misplacement could be identified by comparing the predicted text with the actual text on the golden sample. Experiments on 25 defects and 25 non-defected samples provided a classification accuracy of 97.34%, a precision of 100%, and a recall of 90.70%. Meanwhile, the character error rate (CER) obtained from the test on a total of 57 characters provided a performance of 10.53%. This outcome has implications for developing AOI for various keyboard products. In addition, the precision level of 100% signifies that the proposed method always offers correct results in detecting product defects. Such outcomes are critical in industrial applications to prevent defective products from circulating in the market.
Tiny-YOLO distance measurement and object detection coordination system for the BarelangFC robot Susanto, Susanto; Ricardo Silitonga, Jony Arif; Analia, Riska; Jamzuri, Eko Rudiawan; Pamungkas, Daniel Sutopo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6926-6939

Abstract

A humanoid robot called BarelangFC was designed to take part in the Kontes Robot Indonesia (KRI) competition, in the robot coordination division. In this division, each robot is expected to recognize its opponents and to pass the ball towards a team member to establish coordination between the robots. In order to achieve this team coordination, a fast and accurate system is needed to detect and estimate the other robot’s position in real time. Moreover, each robot has to estimate its team members’ locations based on its camera reading, so that the ball can be passed without error. This research proposes a Tiny-YOLO deep learning method to detect the location of a team member robot and presents a real-time coordination system using a ZED camera. To establish the coordinate system, the distance between the robots was estimated using a trigonometric equation to ensure that the robot was able to pass the ball towards another robot. To verify our method, real-time experiments was carried out using an NVDIA Jetson NX Xavier, and the results showed that the robot could estimate the distance correctly before passing the ball toward another robot.
Co-Authors Adlian Jefiza Ahmad Riyad Firdaus Alvin Analia, Riska Anisatul Munawaroh ANUGERAH WIBISANA Budi Sugandi Budiana, B. Daniel Sutopo Pamungkas, Daniel Sutopo Eka Mutia Lubis Eka Mutia Lubis Fatekha, Rifqi Amalya Fitriyanti Nakul Geminiesty Lathifasari Djavendra Hanjaya Mandala Hasnira, H. Hendawan Soebhakti Heru Wijanarko Ika Karlina Laila Nur Suciningtyas Ika Karlina Laila Nur Suciningtyas Ikhsan, Habyb Nur Jacky Baltes Jefiza, Adlian Julanba, Vafin Kaputra, Aldi Lindawani Siregar Lubis, Eka Mutia Mayang Sari MOCHAMAD ARI BAGUS NUGROHO Mulyadi, Indra Hardian Prasetyo, Naufal Abdurrahman Prayoga , Senanjung Prayoga, Senanjung Puspita, Widya Rika Ricardo Silitonga, Jony Arif Ridwan Ridwan Rifqi Amalya Fatekha Riska Analia Ryan Satria Wijaya S. Susanto, S. Santonius, Santonius Sinaga, Jepelin Amstrong Siti Aisyah Sumantri Kurniawan Risandriya Susanto Susanto Susanto Susanto Utama, Eldio Vivin Oktowinandi Wahyu Wibowo