scholarly journals A Visual Cryptography-Based Watermarking Approach for the Detection and Localization of Image Forgery

Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 136
Author(s):  
Moataz Z. Salim ◽  
Ali J. Abboud ◽  
Remzi Yildirim
Keyword(s):  
Digital Images ◽  
Medical Image Analysis ◽  
Visual Cryptography ◽  
Experimental Results ◽  
Walsh Transform ◽  
Discrete Wavelet ◽  
Image Block ◽  
Geometric Attacks ◽  
Block Based ◽  
Detection And Localization

The usage of images in different fields has increased dramatically, especially in medical image analysis and social media. Many risks can threaten the integrity and confidentiality of digital images transmitted through the internet. As such, the preservation of the contents of these images is of the utmost importance for sensitive healthcare systems. In this paper, the researchers propose a block-based approach to protect the integrity of digital images by detecting and localizing forgeries. It employs a visual cryptography-based watermarking approach to provide the capabilities of forgery detection and localization. In this watermarking scheme, features and key and secret shares are generated. The feature share is constructed by extracting features from equal-sized blocks of the image by using a Walsh transform, a local binary pattern and a discrete wavelet transform. Then, the key share is generated randomly from each image block, and the secret share is constructed by applying the XOR operation between the watermark, feature share and key share. The CASIA V 1.0 and SIPI datasets were used to check the performance and robustness of the proposed method. The experimental results from these datasets revealed that the percentages of the precision, recall and F1 score classification indicators were approximately 97% for these indicators, while the percentages of the TAF and NC image quality indicators were approximately 97% and 96% after applying several known image processing and geometric attacks. Furthermore, the comparative experimental results with the state-of-art approaches proved the robustness and noticeable improvement in the proposed approach for the detection and localization of image forgeries in terms of classification and quality measures.

scholarly journals Copy-Move Forgery Detection in Digital Images using Neural Network

2020 ◽  
Vol 9 (4) ◽  
pp. 1560-1564
Keyword(s):  
Neural Network ◽  
Digital Images ◽  
Experimental Results ◽  
Image Editing ◽  
Forgery Detection ◽  
Software Applications ◽  
Key Points ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
Multiple Stages

Due to easy availability of image editing software applications, many of the digital images are tempered, either to hide some important facts of the image or just to enhance the image. Hence, the integrity of the image is compromised. Thus, in order to preserve the authenticity of an image, it is necessary to develop some algorithms to detect counterfeit parts of an image, if there is any. Two kinds of classic methods exist for the detection of forgery: the key- point based method in which major key points of the image is found and forged part is detected and the block based method that locates the forged part by sectioning the whole image into blocks. Unlike these two classic methods that require multiple stages, our proposed CNN solution provides better image forgery detection. Our experimental results revealed a better forgery detection performance than any other classic approaches.

scholarly journals A Robust Digital Image Watermarking in Hybrid Frequency Domain

2018 ◽  
Vol 7 (3.6) ◽  
pp. 243 ◽  
Author(s):  
P Sridhar ◽  
. .
Keyword(s):  
Signal Processing ◽  
Image Watermarking ◽  
Singular Values ◽  
Scaling Factor ◽  
Discrete Wavelet ◽  
Geometric Attacks ◽  
Host Image ◽  
Hybrid Frequency ◽  
Left And Right ◽  
Block Based

Image watermarking is a method to hide the secret information in a host image for copyright protection of watermark data during the transmission by means of insecure channel. The proposed scheme protects our data with adaptive level of visual quality and robustness against signal processing and geometric attacks. The proposed method divides the host image into four non-overlapping segments labelled as sub-images, DWT is applied on each sub images and then block based DCT is applied on mid frequency channels LH and HL of discrete wavelet transform. Embedded matrix is formed using hybrid transformed coefficients where matrix elements are chosen from the localized two mid frequency coefficients of each block in DCT. SV Decomposition is applied on embedded matrix to factorize it into singular values, left and right singular vectors and embed the scrambled watermark image along with scaling factor in singular value matrix. This repetition of watermark data in each sub-image reduces the PSNR values of the watermarked image. Despite this proposed scheme scales down PSNR value, changing the scaling factor favours to adjust the PSNR to the acceptable level and withstand the signal processing attacks such as JPEG compression and geometrical attack such as rotation, translation. Compared to the other method, the proposed scheme gives better correlation coefficient value for above mentioned kinds of attacks and also provide adaptive PSNR for imperceptibility on watermarked image.  

Robust progressive block based visual cryptography with chaotic map

2016 ◽  
Vol 19 (5-6) ◽  
pp. 1025-1040 ◽  
Author(s):  
Dhiraj Pandey ◽  
Uma Shankar Rawat ◽  
Anil Kumar
Keyword(s):  
Chaotic Map ◽  
Visual Cryptography ◽  
Block Based

Detection and localization of faces on digital images

1994 ◽  
Vol 15 (10) ◽  
pp. 963-967 ◽  
Author(s):  
Gilles Burel ◽  
Dominique Carel
Keyword(s):  
Digital Images ◽  
Detection And Localization

A CRYPTO SIGNATURE SCHEME FOR IMAGE AUTHENTICATION OVER WIRELESS CHANNEL

2005 ◽  
Vol 05 (01) ◽  
pp. 135-148 ◽  
Author(s):  
QIBIN SUN ◽  
SHUIMING YE ◽  
CHING-YUNG LIN ◽  
SHIH-FU CHANG
Keyword(s):  
Packet Loss ◽  
Digital Signature ◽  
Digital Images ◽  
Image Authentication ◽  
Wireless Channel ◽  
Experimental Results ◽  
Signature Scheme ◽  
Original Image ◽  
Degraded Images ◽  
Block Shuffling

With the ambient use of digital images and the increasing concern on their integrity and originality, consumers are facing an emergent need of authenticating degraded images despite lossy compression and packet loss. In this paper, we propose a scheme to meet this need by incorporating watermarking solution into traditional cryptographic signature scheme to make the digital signatures robust to these image degradations. Due to the unpredictable degradations, the pre-processing and block shuffling techniques are applied onto the image at the signing end to stabilize the feature extracted at the verification end. The proposed approach is compatible with traditional cryptographic signature scheme except that the original image needs to be watermarked in order to guarantee the robustness of its derived digital signature. We demonstrate the effectiveness of this proposed scheme through practical experimental results.

A Duplicate Chinese Document Image Retrieval System Based on Line Segment Feature in Character Image Block

2011 ◽  
pp. 14-23
Author(s):  
Yung-Kuan Chan ◽  
Tung-Shou Chen ◽  
Yu-An Ho
Keyword(s):  
Image Retrieval ◽  
Line Segment ◽  
Document Image ◽  
Experimental Results ◽  
Document Images ◽  
Rapid Progress ◽  
Image Block ◽  
Line Segments ◽  
Image Retrieval System ◽  
On Line

With the rapid progress of digital image technology, the management of duplicate document images is also emphasized widely. As a result, this paper suggests a duplicate Chinese document image retrieval (DCDIR) system, which uses the ratio of the number of black pixels to that of white pixels on the scanned line segments in a character image block as the feature of the character image block. Experimental results indicate that the system can indeed effectively and quickly retrieve the desired duplicate Chinese document image from a database.

Tampering Localization in Double Compressed Images by Investigating Noise Quantization

2016 ◽  
Vol 8 (3) ◽  
pp. 46-62
Author(s):  
Archana Vasant Mire ◽  
Sanjay B. Dhok ◽  
Naresh J. Mistry ◽  
Prakash D. Porey
Keyword(s):  
Digital Images ◽  
Forensic Analysis ◽  
Experimental Results ◽  
Quantization Noise ◽  
Svm Classifier ◽  
Compression Process ◽  
Image Tampering ◽  
Compressed Images ◽  
Discrepancy Model ◽  
Uniform Quantization

Noise is uniformly distributed throughout an untampered image. Tampering operations destroy this uniformity and introduce inconsistency in the tampered region. Hence, noise discrepancy is often investigated in forensic analysis of uncompressed digital images. However, noise in compressed images has got very little attention from the forensic experts. The JPEG compression process itself introduces uniform quantization noise throughout an image, making this investigation difficult. In this paper, the authors have proposed a new noise compression discrepancy model, which blindly estimates this discrepancy in the compressed images. Considering the smaller tampered region, SVM classifier was trained using noise features of test sub-images and its nonaligned recompressed versions. Each of the test sub-images was further classified using this classifier. Experimental results show that in some cases, the proposed approach can achieve better performance compared with other JPEG artefact based techniques.

An Algorithmic Approach Based on CMS Edge Detection Technique for the Processing of Digital Images

2020 ◽  
pp. 252-272
Author(s):  
Kalyan Kumar Jena ◽  
Sasmita Mishra ◽  
Sarojananda Mishra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Images ◽  
Color Images ◽  
Experimental Results ◽  
Detection Technique ◽  
Algorithmic Approach ◽  
Current Scenario ◽  
Edge Detection Method

Research in the field of digital image processing (DIP) has increased in the current scenario. Edge detection of digital images is considered as an important area of research in DIP. Detecting edges in different digital images accurately is a challenging work in DIP. Different methods have been introduced by different researchers to detect the edges of images. However, no method works well under all conditions. In this chapter, an edge detection method is proposed to detect the edges of gray scale and color images. This method focuses on the combination of Canny, mathematical morphological, and Sobel (CMS) edge detection operators. The output of the proposed method is produced using matrix laboratory (MATLAB) R2015b and compared with Sobel, Prewitt, Roberts, Laplacian of Gaussian (LoG), Canny, and mathematical morphological edge detection operators. The experimental results show that the proposed method works better as compared to other existing methods in detecting the edges of images.

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