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A Research on Cylindrical Pill Bottle Recognition with YOLOv8 and ORB

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(2), pp.13-20
  • DOI : 10.9708/jksci.2024.29.02.013
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : November 6, 2023
  • Accepted : January 8, 2024
  • Published : February 29, 2024

Dae-Hyun Kim 1 Hyo Hyun Choi 1

1인하공업전문대학

Accredited

ABSTRACT

This paper introduces a method for generating model images that can identify specific cylindrical medicine containers in videos and investigates data collection techniques. Previous research had separated object detection from specific object recognition, making it challenging to apply automated image stitching. A significant issue was that the coordinate-based object detection method included extraneous information from outside the object area during the image stitching process. To overcome these challenges, this study applies the newly released YOLOv8 (You Only Look Once) segmentation technique to vertically rotating pill bottles video and employs the ORB (Oriented FAST and Rotated BRIEF) feature matching algorithm to automate model image generation. The research findings demonstrate that applying segmentation techniques improves recognition accuracy when identifying specific pill bottles. The model images created with the feature matching algorithm could accurately identify the specific pill bottles.

Citation status

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