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Эта публикация цитируется в 4 научных статьях (всего 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
Образец цитирования:
C. Rajalakshmi, M. Alex, R. Balasubramanian, “Copy move forgery detection using key point localized super pixel based on texture features”, Компьютерная оптика, 43:2 (2019), 270–276
Образцы ссылок на эту страницу:
https://www.mathnet.ru/rus/co645 https://www.mathnet.ru/rus/co/v43/i2/p270
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