Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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Data augmentation technique based on image binarization for constructing large-scale datasets

대형 이미지 데이터셋 구축을 위한 이미지 이진화 기반 데이터 증강 기법

  • Lee JuHyeok (School. of Computer Engineering & Applied Mathematics, Hankyong National University) ;
  • Kim Mi Hui (School. of Computer Engineering & Applied Mathematics, Hankyong National University)
  • Received : 2023.02.27
  • Accepted : 2023.03.20
  • Published : 2023.03.31
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Abstract

Deep learning can solve various computer vision problems, but it requires a large dataset. Data augmentation technique based on image binarization for constructing large-scale datasets is proposed in this paper. By extracting features using image binarization and randomly placing the remaining pixels, new images are generated. The generated images showed similar quality to the original images and demonstrated excellent performance in deep learning models.

딥러닝은 다양한 컴퓨터 비전 문제를 해결할 수 있지만, 대량의 데이터셋이 필요하다. 본 논문에서는 대형 이미지 데이터셋을 구축하기 위해 이미지 이진화 기반 데이터 증강 기법을 제안한다. 이미지 이진화를 사용하여 특성을 추출하고 추출된 나머지 픽셀을 랜덤하게 배치하여 새로운 이미지를 생성한다. 생성된 이미지는 원본 이미지와 유사한 품질을 보여주며, 딥러닝 모델에서도 뛰어난 성능을 보였다.

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No.2018R1A2B6009620)

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