Makale detayı · 2019
Detection of Free-Form Copy-Move Forgery on Digital Images
Dergi
Security and Communication NetworksISSN 1939-0114
ISSN kaydı başka bir dergiye işaret ediyor; ad YÖKSİS kaydından.
- Yıl
- 2019
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Security and Communication Networks
- Katalog eşleşmesi (ISSN) Security and Communication Networks (discontinued)
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Nowadays, production and distribution of digital images has become part of our life. Since digital images, which are important carriers of information, are considered as the concrete proofs of facts in many fields and they can be used as evidence in the courts of law, development of techniques to ensure image authenticity is an active research topic. Copy-move forgery is one of the most common manipulation techniques that are implemented on the digital images, and various techniques have been developed for detection of these kinds of forgeries. JPEG format, which presents the ability of making high rate compression without causing remarkable changes in the meaning of the image, is the most commonly used format on digital images. In this study, the topic of detecting free-form copy-move forgeries on digital images is covered. It has been observed that the developed technique is able to detect the professional forgeries in which the copied region is selected in free-form and which are almost impossible to be detected by human eye, with high success rate, and it is able to give successful results even if the image is exposed to postprocesses such as JPEG compression and Gaussian filtering, which make the detection of forgery harder.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
10 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 5 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- A new Copy-Move forgery detection method using LIOP 2022
- Robust Copy-Move Forgery Detection Technique Against Image Degradation and Geometric Distortion Attacks 2023
- Robust Copy-Move Forgery Detection Technique Against Image Degradation and Geometric Distortion Attacks 2023
- Robust Copy-Move Forgery Detection Technique Against Image Degradation and Geometric Distortion Attacks 2023
- Robust Copy-Move Forgery Detection Technique Against Image Degradation and Geometric Distortion Attacks 2023