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Computer Optics, 2019, Volume 43, Issue 2, Pages 270–276
DOI: https://doi.org/10.18287/2412-6179-2019-43-2-270-276
(Mi co645)
 

This article is cited in 4 scientific papers (total in 4 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Copy move forgery detection using key point localized super pixel based on texture features

C. Rajalakshmia, M. Alexba, R. Balasubramanianac

a Dept. of Computer Science, Manonmaniam Sundaranar University, Abishekapatti,Tirunelveli,Tamil Nadu, India
b Dept. of Computer Science, Kamarajar Government Arts College, Surandai
c Dept. of Computer Science & Engg., Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli
References:
Abstract: 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.
Keywords: copy move, segmentation, SIFT, KLSP.
Received: 25.05.2018
Accepted: 25.03.2019
Document Type: Article
Language: English
Citation: C. Rajalakshmi, M. Alex, R. Balasubramanian, “Copy move forgery detection using key point localized super pixel based on texture features”, Computer Optics, 43:2 (2019), 270–276
Citation in format AMSBIB
\Bibitem{RajAleBal19}
\by C.~Rajalakshmi, M.~Alex, R.~Balasubramanian
\paper Copy move forgery detection using key point localized super pixel based on texture features
\jour Computer Optics
\yr 2019
\vol 43
\issue 2
\pages 270--276
\mathnet{http://mi.mathnet.ru/co645}
\crossref{https://doi.org/10.18287/2412-6179-2019-43-2-270-276}
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  • https://www.mathnet.ru/eng/co645
  • https://www.mathnet.ru/eng/co/v43/i2/p270
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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