首页    期刊浏览 2024年11月25日 星期一
登录注册

文章基本信息

  • 标题:Copy move forgery detection using key point localized super pixel based on texture features
  • 本地全文:下载
  • 作者:Rajalakshmi C. ; Rajalakshmi C. ; Germanus Al.M.
  • 期刊名称:Computer Optics / Компьютерная оптика
  • 印刷版ISSN:0134-2452
  • 电子版ISSN:2412-6179
  • 出版年度:2019
  • 卷号:43/2
  • 页码:270-276
  • DOI:10.18287/2412-6179-2019-43-2-270-276
  • 出版社:Samarskii Natsional'nyi Issledovatel'skii Universitet imeni Akademika S.P. Koroleva,Samara National Research University
  • 摘要:The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transform (SIFT) based key point extraction. The experimental result indicates the proposed KLSP approach achieves better performance than the previous well known approaches.
  • 关键词:copy move; segmentation; SIFT; KLSP.
国家哲学社会科学文献中心版权所有