A Novel Image Splicing Detection Algorithm Based on Generalized and Traditional Benford’s Law
TL;DR: On the basis of Benford’s law rich features are extracted from images so that classification process is efficiently performed by a simple SVM classifier short.
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Abstract: Due to the ease of access to platforms that can be used by forgers to tamper digital documents, providing automatic tools for identifying forged images is now a hot research field in image processing. This paper presents a novel forgery detection algorithm based on variants of Benford's law. In the proposed method, Mean Absolute Deviation (MAD) feature is extracted using traditional Benford's law. Also, generalized Benford's law is used for mantissa distribution feature vector. In addition to Benford's law-based features, other statistical features are used to construct the final feature vector. Finally, support vector machine (SVM) with three different kernel functions is used to classify original and forged images. The method has been tested on two common image datasets (CASIA V1.0 and V2.0). The experimental results show that 0.27% and 0.21% improvements on CASIA V1.0 and CASIA V2.0 datasets were achieved, respectively in detection accuracy by the proposed method in comparison to best state-of-the-art methods. The proposed efficient algorithm has a simple implementation. Moreover, on the basis of Benford’s law rich features are extracted from images so that classification process is efficiently performed by a simple SVM classifier short
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Citations
Benford's law applied to digital forensic analysis
TL;DR: In this paper , a statistical model based on Benford's Law was applied to a set of features (colours, textures) extracted from digital images, and the results obtained with a dataset of 18,000 photos, being 9000 authentic and the remaining manipulated.
Image Splicing Detection Using Generalized Whittaker Function Descriptor
Dumitru Baleanu,Rabha W. Ibrahim +1 more
TL;DR: Wang et al. as discussed by the authors proposed a novel image texture feature extraction model based on the generalized k-symbol Whittaker function (GKSWF) for better image forgery detection.
1
Enhancing Book and Document Digitization from Videos: A Feature Fusion-Based Approach
Gaurav Buddhawar,Krupa Jariwala,Chiranjoy Chattopadhyay +2 more
TL;DR: A novel feature fusion-based approach for enhancing book and document digitization from videos is proposed. The approach combines Gray-Level Co-occurrence Matrix (GLCM) features with Thepade's 10-ary texture features (TSBTC) for video frame classification, significantly improving frame selection accuracy and ensuring high-quality digitization.
References
Benford's law : applications for forensic accounting, auditing, and fraud detection
Mark J. Nigrini
- 02 Jan 2012
TL;DR: Benford's Law has been used to detect fraud, errors, and other anomalies as mentioned in this paper, and has been applied to auditing and forensic accounting, even before his groundbreaking 1999 Journal of Accountancy article introducing this useful tool to the accounting world.
347
Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks ☆
TL;DR: A novel multiscale radial basis function (MSRBF) network for forecasting the irregular fluctuation of subway passenger flows is proposed and three empirical studies with special events in Beijing demonstrate that the proposed algorithm can effectively predict the emergence of passenger flow bursts.
214
Image forgery detection using steerable pyramid transform and local binary pattern
Ghulam Muhammad,Munner H. Al-Hammadi,Muhammad Hussain,George Bebis +3 more
- 01 May 2014
TL;DR: A novel image forgery detection method is proposed based on the steerable pyramid transform (SPT) and local binary pattern (LBP) and a support vector machine uses the feature vector to classify images into forged or authentic.
Detecting doubly compressed JPEG images by using Mode Based First Digit Features
Bin Li,Yun Q. Shi,Jiwu Huang +2 more
- 05 Nov 2008
TL;DR: Using the probabilities of the first digits of quantized DCT (discrete cosine transform) coefficients from individual AC (alternate current) modes to detect doubly compressed JPEG images and combining the MBFDF with a multi-class classification strategy can be exploited to identify the quality factor in the primary JPEG compression.
192
Passive detection of image forgery using DCT and local binary pattern
Amani A. Alahmadi,Muhammad Hussain,Hatim Aboalsamh,Ghulam Muhammad,George Bebis,Hassan Mathkour +5 more
TL;DR: A novel passive image forgery detection method is proposed based on local binary pattern (LBP) and discrete cosine transform (DCT) to detect copy–move and splicing forgeries.