Copy Move Forgery using Hu's Invariant Moments and Log-Polar Transformations

Tejas, K; Swathi, C; M, Rajesh Kumar

doi:10.1109/rteict42901.2018.9012293

Cited by 5 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed method also estimates the geometric transformation values with improved reliability and detects multiple forgery operations. The work in [5] uses a high-level algorithm to recognize a unique model of using Hu's invariant moments and Log-polar transformations to minimize feature space dimensionality to one feature per block and parallelly recognizing the CMF among almost the same objects in an image. The qualitative and quantitative outputs obtained demonstrate the effectiveness of the algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimized Image Authentication Algorithm using Redundant Wavelet Transform Based Sift Descriptors and Complex Zernike Moments

Kallath¹,

Lakshmisudha²

2023

IJACSA

View full text Add to dashboard Cite

Due to the advanced multimedia editing tools and supported by sophisticated hardware, creating image/video manipulations for malicious purposes is increasing which is almost impossible to detect manually. Moreover, to conceal the traces, different post-processing operations are performed. Therefore, authenticity is a growing concern and important for identifying original and forged images. One of the popular image manipulations is copy-move forgery in which one or more regions in the image are duplicated to create a malicious effect within an image. The work in this article presents redundant wavelet transform based complex Zernike moment and Scale Invariant Feature Transform (SIFT) keypoint matching technique for copy-move image forgery operation detection. SIFT is robust against scale and rotation that works on identifying similarity using exhaustive search of SIFT features. After extracting SIFT keypoint features agglomerative hierarchical clustering is employed for grouping and key point matching operation is performed. Finally, block matching operation is evaluated and forged regions in the manipulated images are marked and displayed. This work also presents optimized SIFT key-point feature computations resulting in lower computation time, often one of the requirements in real time deployment. The proposed algorithm performance is evaluated using Precision, Recall, F-Measure and average detection accuracy on popular and publicly available MICC-220 database. The proposed technique demonstrates improved speedup and detection rate compared to existing approaches.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Optimized Image Authentication Algorithm using Redundant Wavelet Transform Based Sift Descriptors and Complex Zernike Moments

Kallath¹,

Lakshmisudha²

2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…There are several ways to extract feature from a block or a keypoint retrieved from the previous step. Among them, some commonly used techniques are discrete cosine transform (DCT) [28], discrete wavelet transform (DWT) [29], Fourier transform [30], principal component analysis (PAC) [31], moment-based approaches (for example, Hu [32], Zernike [33], Krawtchouk [34], or PCET moments VOLUME 4, 2016 [35]), and local binary pattern (LBP).…”

Section: B Cmfd Processmentioning

confidence: 99%

Study and Analysis of Copy-move Forgery Detection with Local Binary Pattern Method

RAO

Teerakanok

Uehara

2022

Preprint

View full text Add to dashboard Cite

With the advancement of technology, new problems and challenges also follow, among which the more serious problem is media forgery. Forged media information brings a lot of inconvenience to life. It is difficult to distinguish the truth from the false. In this article, various types of forgery are listed and elaborated with a focus on the copy-move forgery category, the study and research involving copy-move forgery(CMF) detection techniques using the Local Binary Pattern (LBP) are presented. The technical review of recent state-of-the-art LBP-based is provided.

show abstract

“…Hu moment invariants [2] are robust to conventional image processing and image geometric transformation, which can better describe the morphological features in the image. The order moment of the image f (x, y) is defined as:…”

Section: Hu Invariant Moment Extractionmentioning

confidence: 99%

Design of Image Copy-Paste Forensics System Based on Moment Invariants

Shen

Yao

Mei

2021

Int J Innov Educ Res

View full text Add to dashboard Cite

Copy-paste tampering is a common type of digital image tampering, which refers to copying a part of the image area in the same image, and then pasting it into another area of the image to generate a forged image, so as to carry out malicious operations such as fraud and framing. This kind of malicious forgery leads to the security problem of digital image. The research of digital image copy paste forensics has important theoretical significance and practical value. For digital image copy-paste tampering, this paper is based on moment invariant image copy paste tampering detection algorithm, and use Matlab software to design the corresponding tampering forensics system.

show abstract

Copy Move Forgery using Hu's Invariant Moments and Log-Polar Transformations

Cited by 5 publications

References 9 publications

Optimized Image Authentication Algorithm using Redundant Wavelet Transform Based Sift Descriptors and Complex Zernike Moments

Optimized Image Authentication Algorithm using Redundant Wavelet Transform Based Sift Descriptors and Complex Zernike Moments

Study and Analysis of Copy-move Forgery Detection with Local Binary Pattern Method

Design of Image Copy-Paste Forensics System Based on Moment Invariants

Contact Info

Product

Resources

About