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통합공유저작물 검색엔진을 위한 효과적인 비교및 갱신 기법

An Efficient Comparing and Updating Method of Rights Management Information for Integrated Public Domain Image Search Engine

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키워드

주제분류컴퓨터학

초록

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

Abstract

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

참고문헌 (12)

  1. H. Deok-Gi, "A Rights Management Information Updating Technique Using Image Feature Points", Proceedings of the Korean Society of Computer Information Conference, 26(2), pp.462~464 (2018)
  2. "HackerFactor"[URL]
  3. K. hikodukue, "Python NI YORU SCRAPING & KIKAIGA KUSHU KAIHATSU TECHNIQUE", pp.301~320 (2016), Japan-Press
  4. D.G Lowe, "Object recognition from local scale-invariant features", Proceedings of the Seventh IEEE International Conference on Computer Vision, 2, pp.1150~ (1999)
  5. "bskvision"[URL]
  6. A. Krizhevsky, "ImageNet Classification with Deep Convolutional Neural Networks", Proceedings of the NIPS'12 Proceedings of the 25th International Conference on Neural Information Processing Systems, 1, pp.1097~1105 (2010)
  7. S. goki, "Deep Learning from Scratch", pp.227~235 (2016), Japan-Press
  8. 지상엽, "딥러닝 기반의 이미지 분류기 모델에서 학습되지 않은 카테고리 추정 방법", 제어.로봇.시스템학회 논문지, 24(9), pp.793~801 (2018), 제어·로봇·시스템학회[DOI]
  9. K. MyungJoon, "A Study on Big Data Application using Scoring Model", Jounal of Actuarial Science, 7(2), pp.3~22 (2015)
  10. S. Ren, "Faster R-CNN : Towards Real-Time Object Detection with Region Proposal Networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(6), pp.1137~1149 (2017)
  11. EUN-JI SEO, "Integrated Multilayer Metadata Based on Intellectual Information Technology for Customization Services of Public Domain Images with Different Usage Permission of License", Journal of Theoretical and Applied Information Technology, 96(4), pp.1048~1058 (2018)
  12. 남현우, "이미지 저작권 보호 및 이용 활성화를 위한 개선방안에 관한 연구", 한국과학예술융합학회, 15, pp.233~247 (2014), 한국전시산업융합연구원

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