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ЖУРНАЛЫ // Компьютерная оптика // Архив

Компьютерная оптика, 2019, том 43, выпуск 2, страницы 270–276 (Mi co645)

Эта публикация цитируется в 4 статьях

ОБРАБОТКА ИЗОБРАЖЕНИЙ, РАСПОЗНАВАНИЕ ОБРАЗОВ

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

Аннотация: 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.

Ключевые слова: copy move, segmentation, SIFT, KLSP.

Поступила в редакцию: 25.05.2018
Принята в печать: 25.03.2019

Язык публикации: английский

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



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