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JOURNALS // Computer Optics // Archive

Computer Optics, 2019 Volume 43, Issue 2, Pages 270–276 (Mi co645)

This article is cited 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

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

Language: English

DOI: 10.18287/2412-6179-2019-43-2-270-276



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