Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Lidya Rosnita Rosnita
Malikussaleh University
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
IMPLEMENTASI YOLOv8 DAN DEEPSORT DALAM MENGANALISIS KECEPATAN PEMAIN PADA VIDEO REKAMAN SEPAK BOLA: IMPLEMENTATION OF YOLOv8 AND DEEPSORT IN ANALYZING PLAYER SPEED IN FOOTBALL VIDEO RECORDINGS Muhammad Naufal Hadi Silam; Defry Hamdhana Hamdhana; Lidya Rosnita Rosnita
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8474

Abstract

This research develops a computer vision‑based football player speed analysis system integrating YOLOv8 for object detection, DeepSORT for multi‑object tracking, and K‑Means clustering for team identification based on jersey color in the HSV color space. The system processes match videos through preprocessing stages (resizing, color space conversion, and filtering), camera motion compensation using Lucas‑Kanade Optical Flow, and speed calculation with filtering and smoothing mechanisms. Testing on a 30‑second match video demonstrates that HSV‑based K‑Means clustering effectively distinguishes players into two teams with a Silhouette Score of 0.62 and a centroid distance of 5.71°, despite highly similar jersey colors. Speed estimation yields average speeds of 19.7–23.47 km/h, which fall within the high‑speed running category (19.8–25.1 km/h) based on literature, with a maximum speed of 36.2 km/h aligning with professional sprint performance. Comparative analysis proves that HSV is more robust to lighting changes compared to RGB, which fluctuates up to 23 points. The system is implemented as a Flask‑based web application enabling video upload, automated analysis, and annotated video download. Therefore, the system is feasible as an objective and measurable tool for player performance analysis.  
Co-Authors Defry Hamdhana Hamdhana Muhammad Naufal Hadi Silam