A study on pre-processing methods for copy-move forgery detection based on SIFT

Lionnie, Regina; Bahaweres, Rizal Broer; Attamimi, Said; Alaydrus, Mudrik

doi:10.1109/tencon.2017.8228029

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…Many pre-processing methods were combined by Lonnie et al [21] in their proposed scheme. Their pre-processing included HEs and filters (median, Gaussian and sharpening), processed using SIFTs.…”

Section: Figure 2: Digital Image Forgery Detection Techniquesmentioning

confidence: 99%

A Thorough Investigation on Image Forgery Detection

Kumar¹,

Srivastava²

2023

Computer Modeling in Engineering &Amp; Sciences

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Image forging is the alteration of a digital image to conceal some of the necessary or helpful information. It cannot be easy to distinguish the modified region from the original image in some circumstances. The demand for authenticity and the integrity of the image drive the detection of a fabricated image. There have been cases of ownership infringements or fraudulent actions by counterfeiting multimedia files, including re-sampling or copy-moving. This work presents a high-level view of the forensics of digital images and their possible detection approaches. This work presents a thorough analysis of digital image forgery detection techniques with their steps and effectiveness. These methods have identified forgery and its type and compared it with state of the art. This work will help us to find the best forgery detection technique based on the different environments. It also shows the current issues in other methods, which can help researchers find future scope for further research in this field.

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Section: Figure 2: Digital Image Forgery Detection Techniquesmentioning

confidence: 99%

A Thorough Investigation on Image Forgery Detection

Kumar¹,

Srivastava²

2023

Computer Modeling in Engineering &Amp; Sciences

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“…Penelitian deteksi gambar termanipulasi jenis penyerangan copy-move forgery dimulai pada tahun 2017 menggunakan metode scale-invariant feature transform (SIFT) [6][7]. Pada [6], peneliti membandingkan beberapa jarak kedekatan kedua vektor SIFT pada perhitungan perkalian titik untuk membandingkan performa sistem pendeteksian.…”

Section: Penelitian Terdahuluunclassified

“…Pada [6], peneliti membandingkan beberapa jarak kedekatan kedua vektor SIFT pada perhitungan perkalian titik untuk membandingkan performa sistem pendeteksian. Sedangkan pada [7], peneliti membandingkan metode praproses seperti tapis lolos bawah dengan tapis median dan Gaussian, ekualisasi histogram dan tapis lolos atas, untuk membangun sistem pendeteksi gambar termanipulasi berdasarkan metode SIFT. Penelitian menggunakan metode analisis fitur lokal seperti SIFT dimulai di [8] dan disusul pengembangan metode SIFT seperti Reflective SIFT dan MIFT (Mirror Reflection SIFT) di [9][10].…”

Section: Penelitian Terdahuluunclassified

Analisis Metode SIFT dan SURF untuk Sistem Pendeteksi Gambar Termanipulasi Penyerangan Copy-Move Forgery

2018

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Pemalsuan gambar digital telah menjadi salah satu taktik penyebar hoax yang merupakan ajang penyebar provokasi, menimbulkan kerusuhan dan kebencian. Untuk dapat memerangi pemalsuan gambar digital perlu diciptakan sebuah sistem yang dapat mendeteksi gambar tersebut merupakan gambar hasil manipulasi apa tidak. Pada penelitian ini gambar termanipulasi jenis penyerangan copy-move forgery dengan variasi penyekalaan dan rotasi telah dianalisa oleh metode SIFT dan SURF. Hasilnya kedua metode dapat mendeteksi gambar termanipulasi jenis penyerangan copy-move forgery dengan SIFT memberikan hasil dua kali lebih banyak kecocokan dibandingkan SURF dan SURF memberikan hasil pemrosesan waktu 0.33 kali lebih cepat dibandingkan SIFT.

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“…In the pre-processing stage, image data is improved to enhance image features or to reduce undesirable distortions within the image. One of the most commonly used methods at this stage is the conversion of RGB color channels of the input image into a single grayscale image [1], [5][6][7][8][9]. Besides, if the image is stored in a compressed format, the files are decompressed in the preprocessing phase [3].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Copy-move Forgery Detection using Bilateral Filtering

Aksakalli

Kaplan

Kilic

et al. 2020

Balkan Journal of Electrical and Computer Engineering

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Digital image processing methods have a wide area of usage and their complexity is increasing, as well as the tampering methods. A widely used tampering method is copymove forgery. In this study, a hybrid method combining the Discrete Cosine Transform (DCT) and Bilateral filtering is developed. In this method, first overlapping blocks are obtained from the input image. Then, bilateral filtering and DCT of these blocks are multiplied to obtain the refined block features. The block features are scanned by a zig-zag process followed by a lexicographic sorting. Finally, a similarity detection by a predetermined threshold parameter is applied to detect the forgery. Both visual and quantitative results demonstrated that the proposed method can determine the copy-move forgery regions.

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A study on pre-processing methods for copy-move forgery detection based on SIFT

Cited by 5 publications

References 11 publications

A Thorough Investigation on Image Forgery Detection

A Thorough Investigation on Image Forgery Detection

Analisis Metode SIFT dan SURF untuk Sistem Pendeteksi Gambar Termanipulasi Penyerangan Copy-Move Forgery

A Novel Approach for Copy-move Forgery Detection using Bilateral Filtering

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