콘텐츠 본문
논문 국내 국내전문학술지(KCI급) 밝기 변화에 강인한 적대적 음영 생성 및 훈련 글자 인식 알고리즘
- 학술지 구분 국내전문학술지(KCI급)
- 게재년월 2021-08
- 저자명 최동걸
- 학술지명 로봇학회 논문지
- 발행처명 한국로봇학회
- 발행국가 국내
- 논문언어 외국어
- 전체저자수 3
논문 초록 (Abstract)
The system for recognizing text in natural scenes has been applied in various industries. However, due to the change in brightness that occurs in nature such as light reflection and shadow, the text recognition performance significantly decreases. To solve this problem, we propose an adversarial shadow generation and training algorithm that is robust to shadow changes. The adversarial shadow generation and training algorithm divides the entire image into a total of 9 grids, and adjusts the brightness with 4 trainable parameters for each grid. Finally, training is conducted in a adversarial relationship between the text recognition model and the shaded image generator. As the training progresses, more and more difficult shaded grid combinations occur. When training with this curriculumlearning attitude, we not only showed a performance improvement of more than 3% in the ICDAR2015 public benchmark dataset, but also confirmed that the performance improved when applied to our’s android application text recognition dataset.
