Copy-Move forgery detection using EOA, DWT and DCT

Year 2024, Volume: 30 Issue: 2, 222 - 227, 30.04.2024

Ehsan Amiri Ahmad Mosallanejad Amir Sheikhahmadi

Abstract

Copy-move forgery (CMF) is a new challenge because it reduces the accuracy of image forgery detection. In CMFD, we have selected and pasted similar points. The proposed method based on the Equilibrium Optimization Algorithm (EOA), Discrete Wavelet Transform (DWT), and Discrete Cosine Transform (DCT) helps image forgery detection. The method includes feature detection, image segmentation, and detection of forgery areas using the EOA, DWT, and DCT. In the first step, the image converts to a grayscale. Then, with the help of a discrete cosine transform algorithm, it is taken to the signal domain. With the help of discrete wavelet transform, its appropriate properties are introduced. In the next step, the image is divided into blocks of equal size. Then the similarity search is performed with the help of an equilibrium optimization algorithm and a suitable proportion function. Copy-move forgery detection using the Equilibrium Optimization Algorithm can find areas of forgery with a precision of about 86.21% for the IMD data set and about 83.98% for the MICC-F600 data set.

Keywords

Forgery detection, Copy-Move image forgery, EOA algorithm

EOA, DWT ve DCT kullanarak kopyalama-taşıma sahtecilik tespiti

Abstract

Kopyala-taşı sahteciliği (CMF), görüntü sahteciliği tespitinin doğruluğunu azalttığı için yeni bir zorluktur. CMFD'de benzer noktaları seçip yapıştırdık. Denge Optimizasyon Algoritması (EOA), Ayrık Dalgacık Dönüşümü (DWT) ve Ayrık Kosinüs Dönüşümü (DCT) tabanlı önerilen yöntem, görüntü sahteciliğini tespit etmeye yardımcı olur. Yöntem, özellik tespiti, görüntü segmentasyonu ve EOA, DWT ve DCT kullanılarak sahte alanların tespitini içerir. İlk adımda, görüntü gri tonlamaya dönüştürülür. Daha sonra ayrık bir kosinüs dönüşüm algoritması yardımıyla sinyal alanına alınır. Ayrık dalgacık dönüşümü yardımıyla uygun özellikleri tanıtılır. Bir sonraki adımda, görüntü eşit büyüklükte bloklara bölünür. Daha sonra bir denge optimizasyon algoritması ve uygun bir orantı fonksiyonu yardımıyla benzerlik araştırması yapılır. Denge Optimizasyon Algoritması kullanılarak kopyala-taşı sahtecilik tespiti, IMD veri seti için yaklaşık %86.21 ve MICC-F600 veri seti için yaklaşık %83.98 hassasiyetle sahtecilik alanlarını bulabilir.

Keywords

Sahtecilik tespiti, Görüntüyü kopyala-taşıt sahtekarlığı, EOA algoritması

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