SURF ve MSER kombinasyonu ile kopya taşı sahteciliği algılama

Sayısal görüntüler çeşitli veriler içerebildiğinden bilgi paylaşımı için önemli bir kaynak olarak kabul edilmektedir. Ayrıca, görüntüler gerçek hayatta birçok vakada kanıt olarak yaygın olarak kullanılmaktadır. Dijital fotoğrafların popülaritesindeki hızlı artış, teknolojilerin gelişmesinden kaynaklanmaktadır. Dijital görüntüleri değiştirmek için Photoshop ve Corel Photo gibi son yıllarda çeşitli yazılım programları geliştirilmiştir, bu programlar sahtecilik için de yaygın olarak kullanılmaktadır. Teknolojik gelişmeler nedeniyle, insanların sahte görüntüleri çıplak gözle tanıması zordur. Bu nedenle, bu çalışmada, tespit edilmesi zor olan sahte görüntülerin doğru etiketlenmesini sağlamak için sahtecilik tespit problemlerinde sık kullanılan öznitelikler birleştirilmiştir. Hızlandırılmış Sağlam Öznitelikler (SURF) ve Maksimum Kararlı Ekstremal Bölgeler (MSER) birleştirilerek daha güçlü öznitelik elde edilmiştir. Deneysel sonuçlara bakıldığında; kopyala-taşı sahtecilik tespit problemlerinde iki yöntemin birleştirmesi sonucu elde edilen önerilen yöntemin kullanılmasının SURF ve MSER özniteliklerinin ayrı ayrı kullanılması durumuna göre daha başarılı olduğu gözlemlenmiştir.

Anahtar Kelimeler:

Kopyala-Taşı Sahtecilik Tespiti, SURF, MSER, Görüntü Sahteciliği

Copy move forgery detection with SURF and MSER combination

Because digital images may contain a variety of data, they are regarded as an important source for information sharing. Also, images are widely used as evidence in a variety of real-life cases. The rapid rise in popularity of digital photographs is due to the improvement of technologies. Several software programs have been developed in recent years to modify digital images, such as Photoshop and Corel Photo, however these programs are now being used extensively for forgery. Because of technological advancements, it is difficult for people to recognize faked images with their naked eyes Therefore, in this study, the features used in forgery detection problems are combined to ensure accurate labeling of even forgery images that are difficult to detect. Stronger feature is obtained by combining Speeded-Up Robust Features (SURF) and Maximally Stable Extremal Regions (MSER). Considering the experimental results; it has been observed that the use of the proposed method, which is obtained as a result of combining the two methods in copy-move forgery detection problems, is more successful than using the SURF and MSER features separately.

Keywords:

Copy-Move Forgery Detection, SURF, MSER, Image Forensics,

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