Ball Classification through Object Detection using Deep Learning for Handball

Authors

  • Arzielah Ashiqin Alwi Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Ahmad Najmuddin Ibrahim Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Muhammad Nur Aiman Shapiee Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Muhammad Ar Rahim Ibrahim Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Mohd Azraai Mohd Razman Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang
  • Ismail Mohd Khairuddin Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang

DOI:

https://doi.org/10.15282/mekatronika.v2i2.6751

Keywords:

Handball, Accuracy, High Speed Ball, Deep Learning, Object Detection

Abstract

Dynamic gameplay, fast-paced and fast-changing gameplay, where angle shooting (top and bottom corner) has the best chance of a good goal, are the main aspects of handball. When it comes to the narrow-angle area, the goalkeeper has trouble blocked the goal. Therefore, this research discusses image processing to investigate the shooting precision performance analysis to detect the ball's accuracy at high speed. In the handball goal, the participants had to complete 50 successful shots at each of the four target locations. Computer vision will then be implemented through a camera to identify the ball, followed by determining the accuracy of the ball position of floating, net tangle and farthest or smallest using object detection as the accuracy marker. The model will be trained using Deep Learning (DL)  models of YOLOv2, YOLOv3, and Faster R-CNN and the best precision models of ball detection accuracy were compared. It was found that the best performance of the accuracy of the classifier Faster R-CNN produces 99% for all ball positions.

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Published

2020-12-14

How to Cite

[1]
A. A. Alwi, A. N. Ibrahim, M. N. A. Shapiee, M. A. R. Ibrahim, M. A. Mohd Razman, and I. M. Khairuddin, “Ball Classification through Object Detection using Deep Learning for Handball”, MEKATRONIKA, vol. 2, no. 2, pp. 49–54, Dec. 2020.

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Original Article

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