Copy move forgery detection using key point localized super pixel based on texture features
Автор: Rajalakshmi C., Alex Dr. M. germanux, Balasubramanian Dr. R.
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений, распознавание образов
Статья в выпуске: 2 т.43, 2019 года.
Бесплатный доступ
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.
Copy move, segmentation, sift, klsp
Короткий адрес: https://sciup.org/140243289
IDR: 140243289 | DOI: 10.18287/2412-6179-2019-43-2-270-276
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