Probability-based tampering detection scheme for digital images

Hsu, Ching-Sheng; Tu, Shu-Fen

doi:10.1016/j.optcom.2009.12.073

Cited by 62 publications

(27 citation statements)

References 5 publications

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“…One possible application of the proposed comparison method is tamper detection [5,33]. In Figure 8 we show an example, similar to the ones given in [33], of a tampered image with image synthesis attacks. As it appears in Figure 8.d, the algorithm successfully locates the tampered areas.…”

Section: Tamper and Damaged Areas Detectionmentioning

confidence: 97%

New measures for comparing matrices and their application to image processing

Sesma‐Sara

Miguel

Pagola

et al. 2018

Applied Mathematical Modelling

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In this work we present the class of matrix resemblance functions, i.e., functions that measure the difference between two matrices. We present two construction methods and study the properties that matrix resemblance functions satisfy, which suggest that this class of functions is an appropriate tool for comparing images. Hence, we present a comparison method for grayscale images whose result is a new image, which enables to locate the areas where both images are equally similar or dissimilar. Additionally, we propose some applications in which this comparison method can be used, such as defect detection in industrial manufacturing processes and video motion detection and object tracking.

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Section: Tamper and Damaged Areas Detectionmentioning

confidence: 97%

New measures for comparing matrices and their application to image processing

Sesma‐Sara

Miguel

Pagola

et al. 2018

Applied Mathematical Modelling

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“…These dependencies carry important information about the structure of the objects in the visual scene. The SSIM metric, given by (14), is calculated on various windows of an image. The measure relative to two windows x and y of common size (N × N).…”

Section: Perceptual Quality Of Watermarked Imagesmentioning

confidence: 99%

Chaotic watermark for blind forgery detection in images

Benrhouma

Hermassi

El‐Latif

et al. 2015

Multimed Tools Appl

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In this paper, a new chaos based watermarking scheme for effective tamper detection in images is proposed. The proposed scheme is able to detect any possible forgery and spot the areas which have been tampered. To improve the efficiency of the proposed scheme, a binary watermark is constructed from the image itself, which makes the watermark unique for every image and guarantee the blindness in the detection process. To guarantee the security of the proposed scheme, chaotic maps are used to complicate the embedding and the detection process to reduce the vulnerability to different attacks. Experimental results and security analysis show that the proposed scheme achieves superior tamper detection under common attacks.

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“…These approaches often use data embedding techniques [4–8] to achieve the goal of embedment. For example, Hsu and Tu [9] present an image authentication method by embedding authentication information into the least significant bits (LSBs) of image blocks. Their method is capable of detecting and locating tampered blocks of the spatial domain.…”

Section: Introductionmentioning

confidence: 99%

A recoverable AMBTC authentication scheme using similarity embedding strategy

2019

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In this paper, we propose an efficient method for authenticating the absolute moment block truncation coding (AMBTC) compressed images with the capability to recover tampered blocks. The existing methods may not be able to detect some types of intentional tampering. Meanwhile, the tampered blocks are only recovered by their means, causing an unpleasant mosaic-like appearance. The proposed method classifies image blocks into groups according to their similarities, and the group information is recorded for the recovery purpose. The multiple copies of the group information are scrambled and embedded into the bitmap of smooth blocks. The dominant portions of quantization levels are adjusted to generate a set of authentication code candidates. The codes with the minimal distortion are embedded into the least significant bits (LSBs) of the quantization levels. The tampered blocks can be recovered by averaging those untampered ones with the same index. The experimental results show that the proposed method not only achieves an excellent marked image quality and detectability, but also offers a satisfactory recovered result.

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Probability-based tampering detection scheme for digital images

Cited by 62 publications

References 5 publications

New measures for comparing matrices and their application to image processing

New measures for comparing matrices and their application to image processing

Chaotic watermark for blind forgery detection in images

A recoverable AMBTC authentication scheme using similarity embedding strategy

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